Trabajos tooling engineer en Union City, New JerseyCrear alertas

You will join a dynamic team working at the cutting edge of the GenAI revolution by applying AI to AI. You will work on building agents, tools, and models to simplify and accelerate customer adoption of Neuron, the software stack supporting Amazon's Machine Learning silicon: Trainium. Partnering with external and internal customers, you will identify key obstacles and opportunities to accelerate their migration to AWS's ML silicon. You will be a key contributor driving impact by building AI agents and tools that simplify Amazon Neuron adoption, which is critical to Amazon's Generative AI business. Key job responsibilities This role requires collaborating with other Neuron Software teams, Science, AWS AI Services, external partners and customers with a potential high impact on Amazon's top and bottom line. As a member of the team applying Generative AI to accelerate Neuron adoption, you will play a key role in shaping this space with the following technical responsibilities: • Research implementations that deliver the best possible experiences for customers., • Deliver on goals to improve the time and effort it takes to port and optimize Machine Learning workloads on Neuron., • Build and operate agentic evaluation frameworks, monitoring, and feedback loops that ensure the correctness, reliability, and continuous improvement of AI agents, • Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security., • Build high-quality, highly available, always-on products., • Potentially contribute intellectual property through patents About the team We pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs’ location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling. About Amazon Annapurna Labs: Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our Amazon customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design, software and operations. Because of our team’s breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with Neuron, Inferentia and Trainium ML chips, in networking and security with products such as Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with Graviton and F1 EC2 instances. • 3+ years of non-internship professional software development experience, • 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience, • 1+ years of software development engineer or related occupational experience, • 1+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience, • 1+ years of Object Oriented Design experience, • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field, • Experience programming with at least one software programming language, • 3+ years of relevant, broad engineering experience., • Computer Science core: object-oriented design, data structures, and performance analysis with at least 2 programming languages., • Hands-on technical experience working in the Generative AI space, • Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations., • Experience in one or more of the following areas: ML compilers, production coding agents, GenAI model architecture, model training, neural network optimization, or alternatively applied math., • Passion for customer experience and usability, including successful delivery of customer self-service tools and automated management/optimization of services, and a strong services orientation, • 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience, • Bachelor's degree in computer science or equivalent, • Bachelor's or Master's degree in computer science or equivalent, • 2+ years in machine learning or other computational modeling environments with an emphasis on hosting, building or optimizing models for diverse hardware platforms, • Proven track record in building AI agents that automate ML workload optimization, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimization, • Experience working with open-source software communities in the optimization space or related areas, • Domain-level knowledge of AWS services, • Knowledge of the state-of-the-art technology used in the Machine Learning space and its mathematical underpinning Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit _ for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at _. USA, NY, New York - 158,100.00 - 213,800.00 USD annually

Project Description: \n\n • We are looking for a C++ engineer to design and build high performance, low latency applications that process large volumes of real time data. You will work on systems where microseconds and throughput matter, optimizing every layer from algorithms and data structures to networking and OS interaction.\n, • Responsibilities:\n, • • Design, implement, and maintain high performance C++ services handling high message rates and low latency workloads.\n, • • Optimize existing components for latency, throughput, and CPU/memory efficiency.\n, • • Develop and tune networking, messaging, and I/O layers to handle large data volumes reliably.\n, • • Profile and debug performance issues at application, OS, and network levels.\n, • • Collaborate with quantitative, trading, and infrastructure teams (or analogous business/tech teams) to translate requirements into robust technical solutions.\n, • • Write clean, production quality code with appropriate tests and documentation.\n, • • Participate in code reviews, design discussions, and continuous improvement of engineering practices.\n\n \n Mandatory Skills Description: \n\n • • Strong proficiency in modern C++ (C++17/20 or later)\n, • • Solid understanding of concurrency and synchronization (lock free / low lock patterns, atomics, memory models, etc.).\n, • FPGA,colo,co-location\n, • • Proven experience building performance critical, real time, or low latency systems (e.g., networking, trading systems, telemetry, gaming engines, or similar).\n, • • Strong knowledge of computer science fundamentals: data structures, algorithms, memory management, and optimization.\n, • • Practical experience with Linux systems programming (sockets, epoll/select, threads, memory management, CPU affinity, etc.).\n, • • Experience using profiling, benchmarking, and performance analysis tools (e.g., perf, valgrind, flame graphs, CPU/memory profilers).\n, • • Proficiency with version control (Git) and standard build systems (CMake, Ninja, etc.).\n, • • Excellent problem-solving skills and attention to detail; ability to work in a fast-paced environment.\n\n \n Nice-to-Have Skills Description: \n\n • • Experience with kernel bypass or user space networking technologies (e.g., DPDK, RDMA, VMA, Solarflare/OpenOnload) - helpful but not required.\n, • • Experience in financial markets, market data distribution, order routing, or exchange connectivity.\n, • • Familiarity with common market data protocols (e.g., FIX, MDP, ITCH, proprietary exchange feeds) is a plus.\n, • • Experience with multicast, low latency networking, and clock synchronization (e.g., PTP).\n, • • Exposure to hardware aware optimization (NUMA, cache optimization, vectorization/SIMD, CPU pinning).\n, • • Experience with monitoring/telemetry for high performance systems (latency histograms, throughput metrics, SLAs).\n, • • Familiarity with scripting languages (e.g., Python, Bash) for tooling and automation.\n\n

At Guac, we're solving grocery food waste with AI. We forecast exactly how much of each product will sell, helping grocery retailers order and produce the perfect amount of inventory — and we're building AI-native tools that put those forecasts directly into the hands of store operators and buyers. \n \n The grocery industry is enormous (it accounts for 4% of GDP) — and grocery food waste is a huge cost to grocers' bottom lines, but also to our planet. \n \n Today, we're working with major supermarket chains in the US and Canada, and we've scaled to 7-figures in ARR. We're backed by leading investors including Y Combinator, 1984 Ventures, Collaborative Fund, and angels from Open AI, Instacart, and Citadel Securities. \n \n We've brought together an exceptional team from Palantir, BCG, Oxford, Cambridge, and MIT to solve intellectually challenging problems and tackle food insecurity and waste with technology. \n \n We're looking for talented forward deployed engineers in NYC to join our mission. \n About the Role\n \n As a Forward Deployed Engineer at Guac, you'll be the technical bridge between our products and our customers. You'll work directly with grocery retailers — from their IT teams to their store operators — to deeply understand their business, integrate with their systems, and ship custom solutions that make our products work for them. \n \n This isn't a role with tightly-scoped tickets. You'll own customer deployments end-to-end: scoping the integration, building the data pipelines, extending the recommendation engine, and standing alongside customers as we roll out across hundreds of stores. We're looking for engineers who can hold their own in a technical deep-dive with a customer's IT team in the morning, ship production code in the afternoon, and work on our products. \n \n Your responsibilities will include: \n \n Customer & Deployment \n \n\n • Collaborate directly with customers' technical teams to understand their IT infrastructure and integrate with their internal data systems\n, • Work with customers' supply chain and store operations teams to translate their unique business logic into code\n, • Own the end-to-end success of customer deployments, from kickoff through scaling across hundreds of stores\n, • Be the technical face of Guac on the ground — building trust, debugging live, and turning customer feedback into product\n\n \n Data & Backend \n \n\n • Design and build ETL pipelines that process billions of rows of data multiple times per day across customers, using Python, Dagster, and Pub/Sub\n, • Build and extend backend services (Python/FastAPI) that power our ordering and production planning products\n, • Extend our recommendation engine to meet the business needs of each new customer\n, • Expose our data and systems to LLMs via MCP servers, tool-use APIs, and similar protocols\n\n About You\n \n\n • 3+ years of relevant software engineering experience\n, • Strong proficiency in Python and SQL\n, • Proven experience designing and implementing ETL systems across large distributed datasets (Dagster, Airflow, or similar)\n, • Excellent communication skills and a commercial mindset — you've worked directly with customers and can hold your own in a room with both engineers and supply chain VPs\n, • Comfortable operating with ambiguity and minimal process — you thrive when given a problem and trusted to figure out the solution\n, • AI-native: you use Claude Code, Cursor, or similar AI coding tools daily and ship significantly faster because of it\n\n What We Offer\n \n\n • First-hand experience building an early-stage startup with real product ownership\n, • Compensation: $150k–$250k base + competitive equity\n, • Fully employer-paid healthcare (medical, dental, and vision)\n, • Unlimited vacation days\n, • Fully covered food expenses in the office (lunch/dinner)\n, • Free Equinox membership\n\n Our Tech Stack\n \n\n • Languages & Frameworks: Python, FastAPI, SQL\n, • Data & Pipelines: Dagster, Pub/Sub, BigQuery, Postgres, Dask\n, • Cloud & Infrastructure: GCP, Terraform, Docker\n, • AI: MCP servers, Anthropic/OpenAI APIs, agentic tooling\n\n \n Note: this is a 5x day a week in person role in NYC

Position: Sr. Multi-Cloud Infrastructure & Security Architect \n Duration: 12 Months Contract to Hire \n Location: NYC, NY (Hybrid 3 Days a Week Onsite) \n Payrate: $ 75 - 80 per Hour \n \n About the Role and our Mission: \n\n • The Enterprise Email Security team is responsible for safeguarding the email communications for a complex global organization. Although the current team excels in platform architecture, threat mitigation, incident response, compliance, and governance, we are planning a significant transformation of our infrastructure. This initiative involves expanding from a legacy on-premises environment to a robust, multi-cloud ecosystem across leading global cloud service providers.\n, • While the organization possesses deep security expertise, there is a need for a highly skilled professional in cloud architecture and enterprise IT infrastructure to design and implement secure and resilient cloud solutions.\n, • The company is seeking a Senior Multi-Cloud Infrastructure and Security Architect for a full-time contractor role. This individual will serve as a technical leader, translating high-level security requirements into practical, scalable cloud engineering solutions. The role is critical to ensuring the organization’s systems are robust, resilient, and highly available.\n\n \n Key Responsibilities \n 1. Hybrid & Multi-Cloud Architecture Design \n • Architect and implement secure, enterprise-grade multi-cloud infrastructure across AWS and Azure (GCP is a plus), ensuring alignment with benchmarks and corporate security policies. \n • Adopt complex hybrid connectivity solutions to link on-premise and cloud based systems. \n • Establish scalable IAM hierarchies, cross-account trust relationships, and organizational units across multiple cloud tenants. \n 1. Infrastructure Resiliency & Disaster Recovery (DR) \n • Architect high-availability (HA) and disaster recovery topologies across disparate cloud providers to eliminate single points of failure (e.g., active-active cross-cloud replication). \n • Develop, document, and test automated failover mechanisms for critical enterprise workloads to ensure zero-downtime objectives. \n 1. Infrastructure as Code (IaC) & Automation \n • Define, build, and maintain the the IaC repository using automation platforms. \n • Implement secure CI/CD deployment pipelines (Jenkins, GitHub Actions) embedded with automated security guardrails and static analysis tools. \n 1. Technical Advisory & Collaboration \n • Serve as the primary subject matter expert (SME) on cloud infrastructure for the core Cyber Security team, translating security objectives into concrete cloud configurations. \n • Collaborate with traditional on-prem network and sysadmin teams to systematically migrate or extend legacy workloads to the cloud without disrupting active operations. \n \n Required Skills & Experience: \n • Enterprise Scale: Minimum 8+ years of experience managing, architecture-designing, and deploying IT infrastructure within a Fortune 500 or equivalent large-scale enterprise. \n • Multi-Cloud Mastery: Deep, hands-on production experience with at least two major cloud vendors (AWS and Azure are highly preferred). You know their native networking, identity systems, and edge security controls inside out. \n • Networking: Strong foundational background in traditional on-premises networking (firewalls, load balancers, VLANs, proxies) and how those concepts map directly to cloud-native constructs (VPCs, VNets, Transit Gateways). \n • Automation-First Mindset: Advanced proficiency with automation toolsets. \n • Pragmatic Security Knowledge: While you don't need to be a penetration tester, you must thoroughly understand cloud security frameworks and modern identity protocols. \n • Scripting & Systems Proficiency: Strong proficiency with Python programming, Shell scripting, and Unix/Linux operating systems. \n \n Desired Certifications: \n (While your hands-on experience matters most, we highly value the following credentials) \n • AWS Certified Solutions Architect – Professional / AWS Certified Security – Specialty \n • Microsoft Certified: Azure Solutions Architect Expert / Azure Security Engineer Associate \n • CCSP (Certified Cloud Security Professional) or equivalent infrastructure-focused certifications \n \n Preferred / Plus Qualifications: \n\n • Familiarity with Secure Email Gateway (SEG) products such as Proofpoint and Fortimail\n, • Familiarity with Exchange-Online security products such as Sublime security and Abnormal Email Security\n, • Experience with large scale email broadcast or bulk messaging platforms\n, • Exposure to compliance frameworks, audits, and regulatory examinations\n, • Experience integrating email platforms with monitoring, logging, and AIOps tooling\n, • Prior experience mentoring senior or mid level engineers\n\n \n Russell Tobin is a leading minority-owned professional and technical recruitment and staffing advisory organization. We are comprised of specialized practices focusing on a variety of skill sets and industries. Having a depth and breadth of industry expertise, our subject matter experts are able to provide tailored and swift sourcing solutions to fulfill client hiring needs. In other words, we connect top talent with companies. We are the staffing arm of the Pride Global network, a minority-owned integrated human capital solutions firm, with additional offerings in vendor management, payroll programs, and business process optimization. \n Russell Tobin offers eligible employee’s comprehensive healthcare coverage (medical, dental, and vision plans), supplemental coverage (accident insurance, critical illness insurance and hospital indemnity), 401(k)-retirement savings, life & disability insurance, an employee assistance program, legal support, auto, home insurance, pet insurance and employee discounts with preferred vendors. \n \n Equal Employment Opportunity \n Russell Tobin is an equal opportunity employer. We do not discriminate on the basis of the race, religious creed, color, national origin, ancestry, physical disability, mental disability, reproductive health decision making, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age, sexual orientation, veteran or military status, or any other characteristic protected by applicable federal, state, or local law. \n \n Fair Chance Employment \n Russell Tobin is a Fair Chance employer. We consider all qualified applicants, including those with criminal histories, in a manner consistent with applicable state and local Fair Chance laws and ordinances, including, the California Fair Chance Act and all applicable local Fair Chance ordinances. \n \n Accommodations \n We are committed to providing reasonable accommodations to applicants and employees with disabilities. If you require a reasonable accommodation to participate in the application or interview process, or to perform the essential functions of this role, please contact us. \n \n Only applicable for San Francisco Candidates: \n Under the San Francisco Lactation in the Workplace Ordinance, we will provide written notice of lactation accommodation rights, and this notice will automatically be given upon hiring, any inquiry of parental leave or lactation accommodation.

Lawrence Harvey is partnered with a financial services firm that's looking to expand their security team. This client is looking for a D&R Engineer to take ownership of the program and build it from the ground up. \n \n The Opportunity \n We are seeking a Principal Detection & Response Engineer to take ownership of the organization's detection and response capabilities across a complex, highly regulated environment. \n This is a senior individual contributor role with broad technical ownership across the full detection and response lifecycle: from telemetry collection and threat intelligence through detection engineering, AI-assisted triage, investigation, and incident response. \n The ideal candidate is highly hands-on, technically strong, and passionate about engineering detection and response capabilities rather than simply operating them. You will set technical standards, build scalable security tooling, improve automation, and apply AI where it can meaningfully improve security operations. \n \n What You'll Do \n\n • Own the end-to-end detection and response pipeline, including telemetry collection, processing and enrichment, detection, AI-assisted triage, investigation, escalation, and incident response.\n, • Build and maintain an intelligence-informed prioritization framework that translates threat intelligence and organizational risk into prioritized hardening, detection, and automation initiatives.\n, • Develop detections as code, including versioned, tested, peer-reviewed detection logic and pipeline configuration mapped to MITRE ATT&CK or a comparable framework.\n, • Engineer, tune, and operate SIEM, security data pipelines, EDR, SOAR, and case-management platforms to improve signal quality, coverage, reliability, and cost efficiency.\n, • Establish standards for alert triage, investigation, escalation, and response while developing tooling and AI-assisted workflows to support those standards.\n, • Participate in an on-call rotation and remain directly involved in the operational realities of detection and response.\n, • Lead incident response from identification through containment, investigation, remediation, and post-incident activities across corporate, cloud, production, and operational technology environments.\n, • Develop detection and response coverage for threats\n, • Evaluate and implement new security technologies and AI capabilities, including rigorous testing, guardrails, and build-vs-buy-vs-retire recommendations.\n, • Lead tabletop exercises and continuously improve incident response playbooks.\n, • Partner closely with Security Engineering, Infrastructure, Platform, and GRC teams.\n, • Translate technical threats into business risk, security controls, and executive-level communication.\n, • Mentor engineers and help establish a higher engineering standard across the broader security operations function.\n\n \n Required Experience \n\n • 10+ years of experience across security operations, detection engineering, and incident response, including experience building or maturing detection and response capabilities in complex environments.\n, • Strong software engineering skills in Python or Go, including API-driven integrations and automation.\n, • Experience with Infrastructure as Code and detections as code, ideally using Terraform and Git-based development/review workflows.\n, • Proven experience designing, operating, and measuring an end-to-end detection and response program across modern SIEM, security data pipeline, EDR, and automation platforms.\n, • Strong experience detecting and responding in cloud and identity-centric environments, including AWS, Okta or another enterprise identity provider, Microsoft 365 or Google Workspace, and SaaS audit logging.\n, • Strong understanding of attacker tactics, techniques, and procedures, with the ability to translate threat intelligence into high-fidelity detections and prioritized security improvements.\n, • Demonstrated use of AI in security operations, including LLM-assisted investigation and detection development, agentic tooling, and integrations such as Claude Code and MCP.\n, • Strong judgment around AI-generated output, including the ability to identify when models are inaccurate or introducing risk.\n, • Ability to operate at a principal-level IC capacity, setting technical direction and influencing teams without direct authority.\n, • Strong communication skills with the ability to connect threat → risk → control → business impact.\n\n

Overview \n This role lives at the intersection of the customer and the central platform codebase: you’ll work directly with PE portfolio companies to scope, build, and ship AI agents against real operational data, as well as build out the core platform. Half forward-deployed engineer, half platform builder. \n \n What You’ll Own \n\n • Forward Deployment: Embed with customers — PE firms and their portcos — to scope problems, design solutions, and ship AI agents against live operational data.\n, • Solution Engineering: Translate messy, real-world workflows into working systems: entity resolution, workflow inference, and agent deployment.\n, • Customer Trust: Be the technical face in the room — earn credibility with operators and GPs, run demos, and own outcomes end-to-end.\n, • Rapid Prototyping: Stand up POCs and pilots fast using AI-native tooling. •\n, • Feedback Loop: Partner with the CTO and product to close the loop between what you do in the field and the central roadmap.\n\n \n Ideal Background \n\n • Experience: 5–10 years building production software, ideally with direct customer or stakeholder exposure (forward-deployed, solutions/sales engineering, or founding-team work).\n, • AI Nativity: Fluent with modern LLM tooling — coding agents, retrieval, evals, and agent frameworks — and shipping with them daily.\n, • Technical Fluency: Strong in Python and/or TypeScript, comfortable across the stack and with data (SQL, ETL, wrangling messy enterprise systems).\n, • Customer Instinct: Can sit with a non-technical operator, diagnose the real problem, and translate it into a scoped technical solution.\n, • Bias to Ship: Comfortable owning ambiguous, high-stakes deployments end-to-end under time pressure.\n\n \n Bonus Points \n\n • Startup DNA: Early hire or founder; comfortable wearing many hats and owning high-impact work endto-end.\n, • Data Depth: Experience with entity resolution, data unification, or building on modern warehouses/lakehouses such as Snowflake, Databricks, or BigQuery.\n\n \n Key Competencies \n\n • Customer-Obsessed Builder: Equal parts engineer and trusted advisor — motivated by shipping things customers actually use.\n, • Intensity & Resourcefulness: Relentless about getting to the right answer; finds a way through when the path isn’t obvious. •\n, • High Accountability: Communicates clearly, owns outcomes, and thrives in fast-paced, ambiguous environments.\n

JOB TITLE: AI Principal Engineer \n REPORTS TO: Engineering & Product Leadership, Silverside.AI \n Role Type: Full-time hybrid; contract-to-hire with a 30-day mutual evaluation period \n Location: New York, NY (hybrid, regular in-office presence) \n \n Position Summary \n Silverside.AI is seeking an AI Principal Engineer to own architecture and technical direction for its New York engineering pod. This is a hands-on architecture and leadership role focused on designing, building, and scaling the applications and pipelines that power Silverside's AI-driven video and content production systems and agentic workflows. \n \n The ideal candidate is a strong senior technical individual contributor, roughly 4–7 years of professional experience, who has already begun mentoring others, designs systems with real architectural conviction, and communicates effectively in client and internal meetings. Prior VP or extensive people-management experience is not required; this is an opportunity for a high-potential senior engineer to step into formal technical leadership of a high-performing contractor pod while remaining deeply hands-on. \n \n The AP Principal Engineer will set technical direction for a team of senior full-stack developers, drive modular system design, and help shape the product roadmap for the Silverside Experience Engine. \n \n Essential Duties & Responsibilities \n\n • Own architecture and technical direction for the Silverside New York engineering pod, providing clear system design, hands-on mentorship, code reviews, and day-to-day technical oversight so the team delivers high-quality work aligned with product and company goals.\n, • Architect and build scalable full-stack applications, with a strong emphasis on robust backend systems (Python / FastAPI and related modern frameworks), that power AI-driven video and content production pipelines and agentic workflows.\n, • Break complex AI production and agentic workflow challenges into clean, modular, maintainable systems for generation, processing, optimization, and delivery.\n, • Integrate AI/ML models, fine-tuned image and video models, generation APIs, and proprietary workflows into reliable production pipelines.\n, • Set and enforce development standards, testing practices, and deployment discipline across the pod.\n, • Collaborate closely with product, design, and engineering peers to ship full applications and continuously improve AI content systems and internal tooling.\n, • Optimize performance and scalability for high-volume video and media processing workloads.\n, • Troubleshoot and resolve issues in live production environments with urgency and clarity.\n, • Contribute directly to Silverside's growing AI content and agentic workflow ecosystem supporting major enterprise clients.\n, • Present technical architecture, system design decisions, and solution approaches with clarity and confidence in internal roadmap discussions and, when needed, in client or partner meetings.\n, • Partner with C-suite and product leadership on technical prioritization and the evolution of the core platform.\n\n \n Other Duties and Responsibilities \n\n • Provide meaningful, though not primary, client-facing technical presence as needed to support sales, partner, or account conversations.\n\n \n Required Knowledge, Skills, and Abilities \n\n • Bachelor's degree in computer science, engineering, or a related field, or equivalent practical experience.\n, • 4–7 years of professional full-stack development experience, with meaningful hands-on work building production systems involving AI, machine learning, creative media, video, or content generation pipelines.\n, • Strong backend proficiency in Python and modern frameworks (FastAPI, Flask, or Django), with experience designing and operating scalable APIs and services.\n, • Solid secondary frontend skills in contemporary frameworks (React, Svelte, or similar) sufficient to collaborate on and occasionally contribute to user-facing AI tools and interfaces.\n, • Demonstrated ability to design modular, maintainable systems and to discuss architecture with clarity and genuine passion.\n, • Hands-on experience integrating AI/ML models or generation APIs into production workflows, ideally in creative, media, or video contexts.\n, • Experience mentoring or coaching other engineers and raising the bar on code quality, testing, and engineering practices.\n, • Strong written and verbal communication skills, with comfort presenting technical ideas to both technical and non-technical stakeholders, including in client or sales-adjacent settings.\n, • Familiarity with cloud platforms (AWS, GCP, or Azure), containerization (Docker), and modern deployment practices.\n, • Preferred (Nice-to-Have)\n, • Experience with video/media tooling such as FFmpeg, OpenCV, or cloud rendering services.\n, • Prior work in creative industries, AI-generated content, marketing technology, or enterprise digital production environments.\n\n \n Physical Demands \n\n • n/a\n\n \n Salary & Benefits: \n For candidates in New York, the base salary range for this role at the time of posting is $200,000 to $225,000. For candidates in smaller, mid-Atlantic markets, the base salary range for this role at the time of posting is $170,000 to $220,000. The salary an employee or prospective employee is paid within this range will depend on factors such as but not limited to: internal compensation of current employees in similar roles, market considerations, budgetary considerations, level of responsibility, background, experience, and qualifications. \n \n Full-time employees enjoy a competitive benefits package for you and your dependents to ensure a healthy lifestyle. Our benefit offering includes: medical, dental, vision, basic and supplemental life & AD&D, 401(k) with company match, short-term and long-term disability, HSA, and FSA. \n \n Additional Information: \n Silverside AI is an Equal Opportunity Employer and participant in the US Federal E-Verify program. At this time, we are not accepting resumes or candidates from third-party vendors.

Company: RELX Title: Applied AI Engineer Type: 3 to 6 Month Contract to Hire Location: 920 Broadway in Manhattan Type: Hybrid Onsite 4 Days a Week Rate: 90-100/ hour, 170-200k to Convert About the role LexisNexis Legal & Professional is hiring an Applied AI Engineer to help shape the next generation of AI-powered legal products and developer experiences. As an Applied AI Engineer at LexisNexis, you will partner with internal teams and enterprise stakeholders to help build AI-powered applications and workflows on top of LexisNexis AI platforms, legal content, and AI-powered workflows and agent-based capabilities. You will work directly with engineering, AI engineering, and data science teams to design and implement production AI applications, agent workflows, and scalable LLM-powered experiences that support complex legal and professional workflows. This role sits at the intersection of AI engineering, data scientist, developer enablement, and customer engagement. You will partner with Product, Engineering, Applied Science, and AI Platform teams to support implementation decisions, accelerate AI adoption, and help teams adopt reusable AI engineering patterns and implementation best practices. This is a deeply hands-on role focused on building, prototyping, and iterating on AI-powered experiences. The ideal candidate combines strong software engineering fundamentals with practical experience deploying LLM applications, agent systems, and AI-native workflows in production environments. What you’ll do Start with customers • Spend real time with lawyers, legal operations teams, and our internal subject-matter experts — in their offices, on their calls, watching their workflows. Develop a strong understanding of customer workflows and operational challenges through direct engagement., • Translate ambiguous, half-formed customer pain into crisp problem statements the team can build against., • Collaborate closely with customers and internal stakeholders to prototype, validate, and refine AI-powered workflows and user experiences based on customer feedback and observed user needs., • Bring the customer voice back into our roadmaps, our model choices, and our trade-offs., • Occasional travel to customer sites may be required to better understand workflows and gather product feedback. Build AI-powered applications and workflows • Contribute to AI-powered applications and workflows for legal and professional use cases, including leveraging existing RAG pipelines, research assistants, and related AI capabilities developed by ML engineering teams., • Implement and iterate on LLM application capabilities such as prompt engineering, multi-step workflows, tool calling, and lightweight agent patterns in collaboration with machine learning engineering teams., • Contribute to scalable orchestration layers for prompting, retrieval, and tool integration across AI services., • Work with frameworks such as LangChain, LangGraph, LlamaIndex, MCP/A2A, OpenAI SDKs, Google ADK, and/or Anthropic/Claude APIs to prototype and productionize AI capabilities., • Participate in experimentation, testing, and performance optimization activities for LLM-based applications in production environments. Contribute to AI Engineering Enablement • Support adoption of AI engineering practices by helping software engineering teams incrementally integrate machine learning and generative AI capabilities into existing products and workflows, in collaboration with AI/ML engineering teams., • Promote reusable AI/ML engineering standards, tooling, and best practices that reduce friction for teams adopting AI and machine learning technologies, while aligning with recommendations from data science and AI platform teams., • Help software engineers expand their capabilities in ML-oriented development for applicable use cases without requiring deep data science specialization., • Support teams in adopting AI-assisted development workflows through prototyping, architecture collaboration, and hands-on engineering support., • Contribute to engineering for LLM applications, AI workflows, and AI-enabled product development., • Assist in building evaluation, monitoring, and observability tooling to improve AI application quality, reliability, and developer visibility., • Collaborate with Product, Engineering, Data Science, UX, Security, and Legal teams to support the adoption of AI and machine learning capabilities across products and platforms., • Create technical documentation, sample applications, tutorials, and implementation guides to help engineers transition from traditional software development to AI-powered application development., • Partner with engineering teams to introduce modern AI engineering practices, reusable tooling, and machine learning workflows into existing software development processes. Bring others with you • Partner closely with data scientists, machine learning engineers, designers, product managers, legal SMEs, and platform engineering teams. Effective AI product development depends on strong cross-functional collaboration and respect for each discipline’s expertise., • Collaborate with and support engineering teams in adopting modern AI engineering practices, agent workflows, and evaluation approaches., • Communicate clearly with people who aren’t engineers — especially lawyers — and adapt your language to the audience without dumbing things down., • Contribute feedback and implementation learnings to shared AI platform capabilities, tooling, and developer workflows., • Contribute constructively to technical discussions, collaborate effectively across teams, and remain open to feedback and evolving implementation approaches. Required qualifications • 6+ years of experience as a Software Engineer, AI Engineer, Platform Engineer, or related technical role., • Strong production experience building LLM-powered applications and deployment at scale., • Strong programming skills in Python and experience building scalable production services and APIs., • Experience designing and implementing AI application architectures in cloud-native environments., • Hands-on experience with modern AI engineering frameworks and tooling such as LangChain, LangGraph, LlamaIndex, OpenAI APIs, Anthropic APIs, MCP, or equivalent systems., • Experience building AI workflows involving retrieval, tool calling, orchestration, context management, and structured generation., • Familiarity with AI observability, evaluation frameworks, and production monitoring., • Experience deploying and operating AI systems on AWS, Azure, or GCP., • Comfortable working in evolving environments and collaborating across teams to deliver AI-powered features and workflows., • Strong communication and collaboration skills with the ability to work effectively across engineering, product, and business teams., • Experience contributing to production systems and collaborating on practical implementation trade-offs. Preferred qualifications • Experience in legal technology, enterprise SaaS, compliance, financial services, healthcare, or other regulated industries., • Experience building AI copilots, AI assistants, workflow automation systems, or multi-agent platforms., • Familiarity with developer platforms, SDK development, API productization, or AI platform engineering., • Experience facilitating technical workshops, hackathons, or developer enablement initiatives., • Strong understanding of AI UX and conversational workflow system design., • Experience with AI evaluation, guardrails, policy enforcement, and responsible AI deployment., • Familiarity with inference optimization, LLM serving infrastructure, or AI infrastructure tooling., • Full-stack or frontend engineering experience for rapid prototyping and developer experience optimization., • Open-source contributions, technical blogging, conference speaking, or AI engineering community involvement. About LexisNexis Legal & Professional LexisNexis Legal & Professional is a global leader in legal information and analytics, serving customers in more than 150 countries. We are investing aggressively in generative AI, agentic systems, and AI-native workflows that help legal professionals research faster, draft with confidence, and make better decisions in complex legal environments. Our mission is to build trustworthy enterprise-grade AI systems that combine cutting-edge innovation with the accuracy, transparency, and reliability required in the legal industry. LexisNexis is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. The salary range for this position is 170k to 200k. Benefits available to contract/temporary professionals, include medical, vision, dental, and life and disability insurance. Hired contract/temporary professionals are also eligible to enroll in our company 401(k) plan. Visit roberthalf.gobenefits.net for more information. Our specialized recruiting professionals apply their expertise and utilize our proprietary AI to find you great job matches faster.

At Guac, we're solving grocery food waste with AI. We forecast exactly how much of each product will sell, helping grocery retailers order and produce the perfect amount of inventory — and we're building AI-native tools that put those forecasts directly into the hands of store operators and buyers. The grocery industry is enormous (it accounts for 4% of GDP) — and grocery food waste is a huge cost to grocers' bottom lines, but also to our planet. Today, we're working with major supermarket chains in the US and Canada, and we've scaled to 7-figures in ARR. We're backed by leading investors including Y Combinator, 1984 Ventures, Collaborative Fund, and angels from Open AI, Instacart, and Citadel Securities. We've brought together an exceptional team from Palantir, BCG, Oxford, Cambridge, and MIT to solve intellectually challenging problems and tackle food insecurity and waste with technology. We're looking for talented engineers in NYC to join our mission. About the Role As a Backend Engineer at Guac, you'll have real impact and ownership over technical decisions, strategy, and product direction. Your responsibilities will include: • Design and build robust backend services that power mission-critical ordering and production planning products, • Build efficient ETL pipelines to handle billions of rows of data, multiple times per day, • Build AI-powered tools and agents for internal and customer use — exposing our data and forecasting systems via MCP servers, tool-use APIs, and similar protocols so that LLMs can reason over and act on grocery operations data, • Collaborate directly with customers' technical teams to understand and integrate with their IT infrastructure, • Help define how we leverage LLMs across the product surface, from agentic workflows to natural-language interfaces over our forecasts About You • 3+ years of relevant software engineering experience, • Strong proficiency in Python and associated frameworks (FastAPI or similar), • AI-native: you use Claude Code, Cursor, or similar AI coding tools daily and ship significantly faster because of it, • Hands-on experience building with LLMs — tool use / function calling, RAG, agents, or evals — and familiarity with MCP or similar protocols for connecting models to data and systems, • Experience designing and operating data-intensive backend systems (ETL, large-scale pipelines, distributed processing), • (Bonus) Experience in customer-facing technical roles (e.g. forward deployed engineer), • (Bonus) Experience deploying LLM-powered features to production at scale What We Offer • First-hand experience building an early-stage startup, • Compensation: $150k–$250k base + competitive equity, • Fully employer-paid healthcare (medical, dental, and vision), • Unlimited vacation days, • Fully covered food expenses in the office (lunch/dinner), • Free Equinox membership Our Tech Stack • Languages & Frameworks: Python, FastAPI, Dagster, Dask, • Cloud & Infrastructure: GCP, Postgres, BigQuery, Terraform, Docker, • AI: MCP servers, Anthropic/OpenAI APIs, agentic tooling Note: this is an in-person 5 days a week, full time job in NYC.

Role: Staff Software Engineer (Also open to Principal Software Engineers) • Location: New York City (Hybrid 3 days/week out of our office in FiDi / WSA Building), • Type: Full-time, • Reports To: CTO, • Team: Engineering, • Experience Level: 10+ years About SuperCircle Supercircle is the AI-powered operating system for recovering value from billions of unsold and post-sale products across global retail. Brands lose $170B a year to returned, damaged, and excess inventory, and 60% of products and clothing are burned or landfilled within a year of manufacture date. We are unlocking waste as a value generator rather than a cost center, building a new reverse logistics economy for the world’s leading brands. Our AI-powered platform is already the de facto partner for the enterprise market trusted by 100+ brands including J.Crew, VF Corp, GUESS, Reformation, FIGS and Parachute, and has already orchestrated the diversion of 12M+ products from t-shirts to basketballs from landfill while returning $50M+ to our partners' P&Ls. Supercircle is a leading venture backed company in NYC that has raised $40M+ to date from top VCs, including a $24M Series A led by Foundry in 2025 and continuing to grow even faster as we move towards our next round. Led by multi-time co-founders in tech, retail, fashion, and supply chain, Supercircle’s stacked team includes one of the former founders at Gilt Groupe and operators from companies including Flexport, eBay, Equinox, Gap, The RealReal, Afterpay, Meta and Google. We are building the rails for an industry that has, until now, run on spreadsheets and pallets — and we're just getting started on the $170B+ in unmanaged inventory and unrecovered value sitting on brands' balance sheets. About the Role We're looking for a Staff Software Engineer who is a builder first and an engineer second. Someone who gets genuine energy from turning ambiguity into working products, who has already rebuilt their entire workflow around AI, and who asks "why is a human still doing this?" more often than they ask "how should we architect this?" This role is based in New York City. Candidates must be local to the NYC metro area and able to work from our NYC office. We are not considering remote or relocation candidates for this role. You’ll be the anchor of our NYC engineering presence — frequently the only engineer in the office, working alongside a collaborative team and a remote engineering team (for now). This role suits someone deeply self-directed and communicative. What You'll Do • Own and ship meaningful surface area of the SuperCircle platform end-to-end — APIs, web applications, backend services, warehouse and logistics workflows, and partner integrations, • Lead technical design for new domains: schema design, service boundaries, access patterns, and the written-down rationale that outlives the conversation, • Grow into a technical leader for our NYC team — setting direction and eventually mentoring or leading a small group of engineers as we scale here., • Drive and document architectural decisions — RFCs, ADRs, and crisp PR descriptions — and bring the team along with low ego and high conviction, • Build and evolve our AI-assisted development workflow, not just as a participant but as the person who designs how the team uses it safely and at scale, • Mentor and sponsor mid-level and senior engineers through code review, pairing, and direct feedback; raise the bar on testing, observability, and operational discipline, • Engage directly with customers, partners, and commercial conversations — translate what you learn into better product decisions and faster iteration cycles, • Prototype aggressively when the problem is unclear; build for scale when the problem is proven What We're Looking For Experience & Leadership • Typically 8+ years of experience (though we weight trajectory, scope, and ownership over raw tenure) of professional software engineering, with at least 3 years at a staff level at a high-growth or early-stage company, • Demonstrated experience leading technical direction across a team or workstream — you have set the standard, brought others along, and been the person others look to when the hard question has no obvious answer, • A track record of owning systems end-to-end: design, implementation, rollout, on-call, and iteration, • Experience operating close to the product and commercial layers — you have talked to customers, shaped roadmaps, and understood how engineering decisions affect revenue and margin, • Evidence of founder-mode ownership: you have solved problems that weren't your job description because they needed to be solved Builder Mentality • Your instinct when handed an ambiguous opportunity is to prototype, not to ask for requirements, • You are comfortable with incomplete information, changing priorities, and undefined markets — you treat these as inputs, not blockers, • You optimize for outcomes over elegance, and for learning velocity over engineering perfection — without being reckless about it, • You know when to prototype, when to build for production, when to scale, and when to refactor — and you make that call out loud AI-Native Workflow (Non-Negotiable) • You have rebuilt your development workflow around AI — not added it on top, • Daily, hands-on fluency with Claude Code, Cursor, or equivalent agentic coding environments on production codebases, • You have built internal agents, custom skills, MCP servers, or automation tooling for yourself or your team — not as a side project, but as a core part of how you work, • You use AI across engineering, product thinking, research, testing, and documentation — not just for code generation, • You can articulate exactly where AI helps, where it introduces risk, and how to keep human judgment on the decisions that matter, • You think in systems and automation; your default question is "why is a human doing this?" Engineering Fundamentals • Deep TypeScript / Node.js expertise — you have debugged the hard cases and written the postmortem, • Production experience with GraphQL or REST APIs at scale — schema design, query performance, versioning strategy, • Production-grade React and modern meta-framework experience (Next.js, Remix) — SSR/SSG tradeoffs, hydration architecture, • Solid AWS or equivalent cloud fluency — serverless compute, IAM, observability, cost, • Strong NoSQL data modeling — you can design a schema for a domain you've never seen before and defend it under questioning Commercial & Product Instincts • You think from the user backwards — "what is the fastest way to solve the user's problem?" before "how should we architect this?", • You understand revenue, margin, unit economics, and enterprise sales cycles — and you enjoy it, • You ask "how does this help us close another $500k account?" as naturally as you ask technical questions, • You can run customer discovery, design workflows, and prototype interfaces — not just build what someone else spec'd Nice To Have • Experience with reverse logistics, supply chain, warehouse management, or RFID systems, • Multi-tenant SaaS, partner-scoped data, or RBAC at scale, • Past work re-platforming a system that outgrew its original architecture without stopping the train, • Shipped internal AI tooling that made your team measurably faster or safer — lead with this in your application How You Work • You write clearly — design docs, RFCs, and Slack threads are part of how you lead, • You have strong opinions and weak attachment — you can debate hard and align fast with no drama, • You push back on premature abstraction and scope creep, and you make that call out loud, • You feel personal responsibility for company outcomes, not just your ticket queue, • You are direct, low-ego, and focused on finding the right answer — not on being right Why SuperCircle We're the de facto technology and supply chain infrastructure for the post-sale economy. 100+ brands run on our physical AI network to route returns, excess, and trade-ins to their highest-value outcome, and we've already returned $50M+ to their P&Ls. As part of our team, you'll have the rare chance to be a market maker in a category where market, AI, and policy tailwinds are converging at once. If you're ready to define an industry and build with us, let's talk. Ready to join the revolution? Apply now and help us reshape the future of fashion and circular commerce. Email resume to ashley@supercircle.world and include the position you are applying in the subject line of your email. COMMITMENT TO DIVERSITY: SUPERCIRCLE is committed to bringing together individuals from different backgrounds and perspectives. We strive to create an inclusive environment where everyone is welcome, is celebrated for being themselves, and can succeed together. SUPERCIRCLE is an Equal Opportunity Employer, providing equal employment and advancement opportunities to all individuals. We recruit, hire and promote into all job levels the most qualified applicants without regard to race, color, creed, national origin, religion, sex, age, disability, gender identity, sexual orientation, military service, caregiver status, credit history, immigration status, or any other status protected under applicable law.

Title: Senior AI Engineer (Palantir Foundry, Agentic AI) Location: New York City area preferred; open to candidates based on East Coast that are willing to travel Target Start Date: ASAP Type: C Salary / Pay Rate: $100/hr Why Work Here This is a data and AI consultancy where engineers are trusted with real ownership from day one. You will be included in decisions, work directly with senior leadership, and never be micromanaged. The team works as an official Claude partner and builds with modern AI tooling every day, so you will spend your time solving hard problems rather than fighting outdated processes. It is a place for people who want their work to matter and to see it used by real people. About the Role We are building a team of 6 to 8 AI engineers for a brand new, greenfield engagement expected to run about 15 months. The work is focused on the Palantir Foundry platform and on agentic AI systems that will be shipped to real end users, not left as prototypes. The client is private equity backed, so timelines are short and use cases are narrowly focused, which rewards engineers who can move quickly and deliver working software. You will own meaningful parts of the build end to end, from data engineering and semantic modeling through deployment of production LLM workflows. Responsibilities • Design, build, and deploy agentic AI and LLM workflows that run in production and serve real end users, • Develop data pipelines, ontology, and applications on the Palantir Foundry platform, • Build and maintain the semantic layer that connects enterprise data to AI agents and applications, • Implement infrastructure as code and CI/CD pipelines to support reliable, repeatable releases, • Deliver focused use cases on short timelines, prioritizing working software over extended prototyping, • Use AI-assisted development tools, including Claude, to accelerate engineering and delivery, • Monitor, troubleshoot, and improve AI systems once they are live, • Work directly with client stakeholders and leadership, taking ownership of outcomes with minimal oversight Required Skills, • Has shipped at least one agent or LLM workflow that reached real users or a live production system (prototypes, demos, and hackathon projects alone do not meet this requirement), • Roughly 6 to 12 years of engineering experience, • 2+ years of hands-on AI/ML engineering experience, • Hands-on experience with Palantir Foundry, • Strong working knowledge of LLMs and agentic AI frameworks and patterns, • Data engineering experience building and maintaining production pipelines, • Experience with infrastructure as code and CI/CD, • Experience designing or working with a semantic layer Bonus / Soft Skills, • Deep experience with Claude and Anthropic tooling, • Consulting or client-facing delivery background, • Comfortable owning work independently in a fast-moving, greenfield environment, • Experience supporting private equity backed or high-urgency engagements, • Financial services or insurance industry exposure, • Clear communicator who can explain technical tradeoffs to business stakeholders Welcome to ConsultNet, a premier national provider of technology talent and solutions. Our expertise spans across project services, contract-to-hire, direct search, and managed services onshore, nearshore, and hybrid. For over 25 years, we have connected thousands of consultants with meaningful roles through a personal, communication-driven approach, partnering with a diverse client base to build high-performing teams and create lasting impact. Our comprehensive service offerings cover a wide range of technology and engineering positions across key markets nationwide. Learn more at _ . We champion equality and inclusivity, proudly supporting an Equal Opportunity Employer policy. We welcome applicants regardless of Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other status protected by law.

Company Description Meridian brings context-aware AI agents to industries that have traditionally been overlooked in technology adoption such as supply chain, manufacturing, staffing and more. The company works closely with sector experts to automate operations, enhance decision-making, and unlock new efficiencies through applied AI. Meridian is backed by leading investors, including Sunflower Capital, Pear VC, SV Angel, and angels from Anthropic. Team members join a fast-moving environment where they can shape products from the ground up and see their work deployed directly in critical industry workflows. \n \n Role Description The Software Engineer role at Meridian is a full-time, on-site position based in New York, NY. In this role, the engineer designs, builds, and maintains backend systems and services that power AI-driven products, with a focus on performance, reliability, and scalability. Day-to-day responsibilities include writing clean, maintainable code, implementing APIs, integrating data sources, and collaborating with product and AI teams to translate requirements into technical solutions. The role also involves participating in code reviews, improving development processes, and troubleshooting production issues to ensure smooth operation of customer-facing systems. Engineers are expected to contribute to architectural decisions, documentation, and continuous improvement of the overall software stack. \n \n Qualifications \n\n • Strong foundation in Computer Science, including algorithms, data structures, and systems fundamentals.\n, • Proficiency in Software Development and Programming, with experience shipping production-quality code.\n, • Hands-on experience in Back-End Web Development, including building and maintaining APIs and services.\n, • Solid understanding of Object-Oriented Programming (OOP) principles and their application in modern codebases.\n, • Experience with Python, TypeScript and relational or NoSQL databases.\n, • Comfort working in Linux-based environments, using version control (Git) and standard development tooling.\n, • Ability to collaborate in a cross-functional team, communicate clearly, and take ownership of projects from design through deployment.\n, • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience; prior experience with AI/ML systems or data-intensive applications is a plus.\n

\n • Full time\n, • Perm\n, • On site in NYC - Midtown East Manhattan - 5 days a week\n, • $200K base + very generous bonus\n\n \n C++ Engineer (Market Access) \n \n We are seeking a highly skilled C++ Engineer with deep expertise in low-latency market access systems to design, build, and optimize connectivity to global exchanges. This role is ideal for an engineer with extensive experience in modern C++, performance-critical systems, and electronic trading environments, who wants to work on ultra-fast, mission-critical infrastructure. \n Responsibilities \n\n • Design, develop, and optimize low-latency market access gateways and exchange connectivity components.\n, • Implement new exchange protocols, order entry, and market data handlers across global markets.\n, • Enhance performance through micro-optimizations, lock-free programming, CPU/memory profiling, and latency-reduction techniques.\n, • Collaborate closely with traders, quants, and infrastructure teams to deliver robust, high-performance trading systems.\n, • Maintain and improve reliability, throughput, and system observability across all market access components.\n, • Participate in full software lifecycle: design, testing, deployment, monitoring, and incident response.\n\n Qualifications \n\n • Expert-level C++ (C++17/20), with deep knowledge of templates, STL internals, optimization, concurrency, and memory models.\n, • Extensive experience working in finance, ideally in market access, HFT, low-latency trading, or market data systems.\n, • Strong understanding of network programming, kernel bypass technologies, multicast,\n, • TCP/UDP, and high-performance messaging.\n, • Hands-on experience with Linux internals, performance tuning, CPU affinity, and profiling tools.\n, • Experience with exchange protocols (OUCH, FIX/FIXP, binary protocols, proprietary APIs).\n, • Ability to work in high-pressure, rapid-iteration environments with a focus on precision and stability.\n, • Bachelor's or Master’s degree in Computer Science, Electrical Engineering, or related technical field.\n\n Preferred Experience \n\n • Background in equities, options, futures, or FX market structure.\n, • Experience with packet capture/analysis, kernel tuning, and ultra-low-latency optimization.\n, • Familiarity with Python for tooling and automation.\n, • Experience improving end-to-end system performance: networking, hardware, OS, and application layers.\n\n

The role \n We're hiring a founding AI engineer to help design insight and discovery extraction models and ship tools for scientists. You’ll own the architecture and build the ML stack alongside our Chief Science Officer and work directly with the founders. \n \n What you'll do \n\n • Ship enterprise-ready products across our platform: data capture, structured experimental records, querying, and analysis tools\n, • Build our AI systems: multimodal pipelines (vision models for handwritten notebook pages and drawn structures, speech-to-text at the bench), agents that reason over a lab's full experimental history, and models that predict outcomes and propose optimized process conditions\n, • Work directly with research partners; watch scientists use what you built, then improve it\n, • Help shape model architecture, data pipelines, and technical direction as an early team member\n, • Build the data engine that turns messy experimental data (synthesis notes, PXRD, characterization) into training-grade datasets\n\n \n What we're looking for \n\n • 1+ years of experience managing technical projects at startups and team members or big companies / research labs (e.g., FAIR Chemistry, Google DeepMind, Microsoft Research, OpenAI, Anthropic Lila Sciences, MIT/Stanford/Berkeley/CMU/UToronto AI-for-science groups, or similar)\n, • Deep in at least two of: geometric deep learning (E(3)/SE(3)-equivariant GNNs), generative models (diffusion, flow matching), ML interatomic potentials\n, • A track record of shipping enterprise-ready products to real users, end to end, with FDE / customer facing technical experience a plus\n, • Comfort across the stack: you can get a feature all the way out the door & bias toward speed and ownership in a small, fast-moving team\n\n \n Logistics: NYC in-person (negotiable for the right person). US work authorization required. \n \n Nice to have: model architecture/fine-tuning experience; background in chemistry, materials science, or scientific tooling; familiarity with scientific data (spectra, diffraction patterns, instrument output), A first-author or major-contributor paper in ML-for-science, geometric ML, molecular/crystal generation, scientific agents, interatomic potentials, synthesis planning, or active learning. \n \n About 83 Sciences \n 83 Sciences (YC S26) is the intelligence engine powering the future of research and materials discovery. Most experimental data (failed runs, unpublished results, raw instrument output) never gets captured. We turn raw lab signals into novel discoveries: capturing and structuring experimental data, shortening research processes, and surfacing the insights that drive new materials.

Our client in Dallas, TX, is seeking a Lead Full Stack Engineer to join their team! \n \n This is an onsite/full-time/direct-hire position \n Salary range based on experience: $130K-$140K \n \n Our client is seeking a Principal Full Stack Engineering Lead Consultant to direct delivery, guide modern frontend and backend architecture, and drive measurable client outcomes for enterprise platform initiatives. This role operates at the intersection of hands-on software development, system design, AI-assisted software engineering, agentic architecture, and technical leadership. You will lead cross-functional engineering teams through application modernization and enterprise platform delivery while serving as a trusted technical point of contact for client stakeholders. \n \n Your Impact \n\n • Lead the architectural design and delivery of secure, scalable enterprise applications using modern Angular frontends and Java enterprise microservices.\n, • Modernize legacy application architectures into modular, microservices-driven, and event-driven architectures.\n, • Drive the adoption of AI-enabled engineering workflows and agentic capabilities, incorporating RAG integration, MCP (Model Context Protocol) server architectures, and automated testing practices to accelerate time-to-market.\n, • Elevate team throughput, code quality, and delivery predictability by setting strict engineering guardrails, design patterns, and testing standards.\n, • Act as a primary technical contact for client leadership, aligning technical roadmaps with business objectives and stakeholder priorities.\n\n \n What You Will Do \n\n • Provide hands-on technical leadership across the software development lifecycle, defining frontend and backend architecture, engineering standards, and technical strategy.\n, • Lead the architectural design and development of enterprise applications using Angular 16+, TypeScript, RxJS, state management, and component design systems.\n, • Architect and develop secure backend microservices, RESTful APIs, and integration layers using Java 11/17+, Spring Boot, and enterprise authentication protocols (OAuth2, JWT).\n, • Design and execute advanced AI integrations, including Agentic RAG patterns, custom MCP (Model Context Protocol) server connections, enterprise vector database RAG pipelines, and AI-assisted developer tooling (GitHub Copilot, Claude Code, TestPilot AI).\n, • Direct, mentor, and elevate an engineering team, establishing delivery practices, code review standards, WCAG 2.1 AA accessibility compliance, CI/CD pipelines, and observability practices.\n, • Translate business requirements into architectural decision records (ADRs), technical roadmaps, and actionable execution plans in close collaboration with client Product Managers and UX teams.\n\n \n What You Will Bring \n Must Have Experience \n\n • 12+ years of professional software engineering experience, with 8+ years dedicated to enterprise-scale Angular application development (Angular 14+, TypeScript, RxJS, state management, SCSS, responsive design).\n, • 5+ years of enterprise backend engineering experience using Java 11/17+, Spring Boot, RESTful APIs, microservices architectures, and relational or NoSQL database integration.\n, • 3+ years in formal technical leadership positions (Principal Engineer, Tech Lead, Staff Engineer) with direct experience guiding engineering teams and defining system architecture.\n, • Applied experience with advanced AI integrations and agentic architectures, including production RAG integration, Agentic RAG workflows, and MCP (Model Context Protocol) Server implementation or integration, alongside AI-assisted development tools (e.g., GitHub Copilot, Claude Code, OpenAI APIs).\n, • Deep expertise in frontend performance optimization (lazy loading, change detection, caching), Web Accessibility standards (WCAG 2.1 AA / ADA compliance), and enterprise design systems.\n, • Strong hands-on experience with automated testing frameworks (Cypress, Jest, Jasmine, Karma, JUnit) and enterprise CI/CD pipelines (GitHub Actions, Jenkins, Docker).\n, • Proven track record of working directly with enterprise client stakeholders to drive architectural decisions and deliver business results.\n\n

Machine Learning Performance Engineer (Inference) \n High-Frequency Trading Firm \n Compensation: $600,000-1.5 million total \n \n About the Opportunity \n A leading high frequency trading firm is hiring a Machine Learning Performance Engineer to sit at the intersection of quantitative research and high-performance production systems. In his role, you'll architect inference pipelines that operate at the physical limits of hardware, driving the speed, efficiency, and reliability of ML inference so predictive models consistently achieve microsecond-level latency. \n \n GPU usage across the firm's trading teams has grown roughly 100x in the past year as deep learning has moved from a supporting signal to the core of how strategies are built. That growth has outpaced the decision-making around it. Strategies get pushed onto GPUs by default, without anyone systematically asking whether GPU is the right target at all. This role owns that question end to end: benchmark the workload across CPU, GPU, and FPGA, decide the architecture on evidence, then optimize and deploy against it. \n \n You will also have the chance to revisit existing models that never reached production, some of which stalled for hardware or deployment reasons, and run them through different environments to determine where they belong. \n \n What You'll Do \n Benchmarking & Strategy \n\n • Lead the technical evaluation of inference platforms across CPUs, GPUs, and FPGAs to guide infrastructure deployment decisions\n, • Benchmark trading workloads across architectures before compute is committed, and identify where performance gains actually come from — code-level or hardware-level\n\n System Architecture Optimization \n\n • Analyze and enhance execution across deep memory hierarchies to maximize resource utilization and parallel processing\n, • Assess and resolve memory subsystem and interconnect bottlenecks across the end-to-end inference lifecycle\n\n Infrastructure & Deployment Feasibility \n\n • Work with Infrastructure teams to understand the thermal, power, and operational constraints of hardware platforms, and design inference strategies for latency-critical trading strategies that fit within those envelopes\n, • Consider the interaction between trading workloads, compute requirements, hardware selection, and fleet utilization\n\n GPU Kernel Development \n\n • Develop highly optimized kernels and integrate specialized performance libraries to extract maximum computational throughput from the underlying silicon\n\n Model Optimization & Deployment \n\n • Implement advanced model reduction techniques — quantization, pruning, distillation — to ensure compact memory footprints and numerical stability\n, • Prioritize optimization for low-latency, event-level inference workloads that meet real-time trading requirements\n\n Cross-Functional Collaboration \n\n • Partner closely with ML Researchers, HPC Engineers, FPGA Engineers, and Datacenter Engineers to bring target deployments to production\n\n \n What We're Looking For \n\n • 2+ years optimizing deep learning inference in latency-sensitive or high-throughput production environments, in any domain\n, • ML frameworks: deep expertise in lower-level ML framework development (PyTorch/JAX), paired with strong Python/C++ skills and a thorough understanding of mixed-precision computation\n, • Kernel development and tooling: proven experience building custom GPU kernels, with deep familiarity with optimization libraries and compilers (Triton, TensorRT, ONNX, IREE, HLS4ML, cuBLAS, CUTLASS) and profiling tools (Nsight Systems, Nsight Compute)\n, • GPU architecture: deep expertise in GPU microarchitecture, including SM execution, warp scheduling, and full memory hierarchy optimization from registers to HBM\n, • Cross-architecture benchmarking: a rigorous, data-driven track record evaluating inference performance across heterogeneous compute architectures\n, • Prior experience in financial trading is not required.\n\n \n Nice to Have \n\n • Practical experience targeting and optimizing inference workloads on specialized hardware ecosystems, including FPGAs and ASICs\n\n \n Why Join? \n This is a role with genuine decision-making scope. Rather than optimizing code for whatever hardware happens to be available, you will determine which hardware the workload should run on in the first place, prove it with data, and then build for it. That combination of architectural judgment and hands-on kernel, and the results are measurable in production almost immediately. \n You'll work on inference at microsecond latency, where the constraints are physical rather than theoretical, and where memory hierarchy, interconnect behavior, thermal envelopes, and fleet utilization all shape the answer. \n \n Benefits include generous paid time off, regional savings and financial wellness plans, hybrid working options, free breakfast, lunch, and snacks daily, in-office wellness experiences and reimbursement for select wellness expenses, company-sponsored sports teams and fitness events, volunteer and charitable giving opportunities, regular social events, and ongoing workshops and learning opportunities. \n \n The culture is collaborative and low on hierarchy, smart, driven people, an open-plan workspace, casual dress, and an environment where the best idea wins. \n \n Equal opportunity employer.

MrSteam is looking for an early-career Mechanical Design Engineer who enjoys hands-on product work and wants to grow into broader engineering ownership over time. \n This is a great opportunity for someone who likes to understand how products actually work - not just design them on screen. \n You'll work across: \n\n • SolidWorks 3D modeling and 2D drawings\n, • Product testing, lab setup, and technical reporting\n, • Sustaining engineering and product improvements\n, • Manufacturing and tooling support\n, • Troubleshooting mechanical, plumbing, and electrical product issues\n, • Supplier and technical-service support\n, • Cost and value-engineering projects\n\n What we're looking for \n\n • Hands-on mechanical engineering aptitude\n, • SolidWorks experience\n, • Strong engineering problem-solving skills beyond CAD\n, • Comfort working with physical products, testing, and troubleshooting\n, • Mechanical Engineering background preferred\n, • HVAC, appliance, plumbing, or similar product experience is a plus\n, • 0-5 years of experience, including strong recent graduates\n\n What success looks like \n During the first year, you'll build deep knowledge of MrSteam products, take on increasingly independent engineering assignments, and develop toward ownership of defined design, testing, sustaining, and product-support projects. \n If you're an engineer who enjoys building, testing, troubleshooting, and learning how things work, I'd love to connect.

If you have previously applied for this role - we have your application, please do not reapply \n \n Location: In Office (NYC) Mon - Thurs. \n Employment Type: Full-time \n Visa Sponsorship / Transfers: We cannot sponsor H1B lottery applications (F1 / OPT etc.) \n \n About Domify \n Domify works with some of the largest financial institutions in the country to transform how compliance and regulatory oversight is conducted. We deploy our AI agents and orchestrations to solve a variety of compliance and operational challenges, bringing scale, cost efficiencies and a high degree of determinism to the process. \n \n Location: NYC in-office \n We expect the successful candidate to work from Domify's FiDi office NYC 4 days a week. Telecommuting, short NYC stays or relocation are not in consideration at this time. \n \n About the role \n We are looking for an all-round, hands-on Senior Platform Engineer to own and build out our AI infrastructure - whether on-prem (hosted by our clients in their environments) or our own SaaS offering. The ideal candidate will be comfortable facing off with client DevOps and Infra teams, and have extensive experience deploying enterprise grade infra. They will also have the opportunity to step in and help colleagues build and ship product-grade AI features. Some client on-site travel may be required as needs arise, in a quasi-FDE role. \n \n What you will do (required skills): \n\n • Build and operate Kubernetes (EKS) workloads, plus portable deployments that run inside client environments across cloud providers.\n, • Own our infrastructure as code in Terraform, building modular, reusable configurations for both our infrastructure and our clients'.\n, • Manage release delivery with Helm and build CI/CD pipelines in GitHub Actions covering build, test, scan, and deploy.\n, • Stand up observability — telemetry, logging, alerting, and on-call-ready dashboards — using AWS-native tooling and EKS log pipelines.\n, • Run PostgreSQL in production: connection pooling, query and index tuning, backups, replication, and failover.\n, • Forward-deploy the stack into client infrastructure and contribute to product engineering (Python, React) as startup priorities demand.\n\n \n Required Skills and Qualifications: \n\n • A minimum of 5yrs of work experience in enterprise software and deployments.\n, • Production Kubernetes on EKS and deep AWS experience, plus working competence in a second cloud and a track record of cloud-agnostic deployments that run outside your own account.\n, • Strong command of infrastructure as code and delivery tooling: Terraform, Helm, GitHub Actions, and Docker.\n, • PostgreSQL operations — load management, tuning, replication, backup and restore — and observability across AWS and Kubernetes.\n, • Python strong enough to contribute to product code, on top of solid Linux, networking, and security fundamentals.\n\n \n Good to have: \n\n • Prior experience with enterprise FinTech, preferably in an AI / ML role\n, • A degree in Computer Science, Engineering, or a related field (BSc/MSc)\n, • Hands-on experience with new product delivery, ideally within startups.\n, • Domain expertise in financial services, wealth and investment management\n\n \n What We Offer: \n\n • A pivotal role in a rapidly growing startup set to reshape regulatory compliance.\n, • The opportunity to work with a diverse group of successful and motivated colleagues and advisors from the industry.\n, • Substantial equity stake in an early stage startup, aligning your success with ours, competitive base salary, and health benefits.\n, • A chance to shape the future of AI technology alongside a diverse and talented team.\n\n

Hybrid until Jersey City goes fully onsite in Jersey City, NJ \n \n Our client seeks a Java/AWS Engineer to develop Kafka-based event-driven applications and RESTful APIs within a high-throughput, low-latency brokerage processing domain. The role will design and build reusable microservices on AWS while supporting modernization from legacy systems to cloud-native solutions. You will apply CI/CD practices, containerization, and automation testing to deliver scalable, resilient services. \n \n Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. \n \n Rate: $85.00 to $90.00/hr. w2 \n \n Responsibilities \n\n • Design, architect, and build scalable, low-latency event-driven services using Java, Spring Boot, and Apache Kafka.\n, • Develop and maintain RESTful APIs and microservices with a focus on reusability and high throughput.\n, • Leverage AWS managed services, containerization, and infrastructure automation to deploy resilient applications.\n, • Implement CI/CD practices including feature toggles, blue-green deployments, and A/B testing to reduce risk and cycle time.\n, • Create automation testing with frameworks such as Cucumber to ensure quality and reliability.\n, • Participate in technical discussions and provide guidance to accelerate modernization squads.\n, • Optimize data access using Hibernate/JDBC and connection pooling with relational databases.\n, • Build and operate observability with CloudWatch and related tooling to ensure service health.\n\n \n Experience Requirements \n\n • 6+ years of professional experience with Java and Spring Boot.\n, • Hands-on experience building event-driven applications with Apache Kafka.\n, • Proficiency in designing high-throughput, low-latency distributed systems.\n, • Experience developing RESTful APIs and microservices with Spring Boot.\n, • Hands-on experience with container-based development using Docker.\n, • Experience with Hibernate ORM, JDBC, and connection pooling against relational databases.\n, • Experience with CI/CD tools and practices such as GitHub, Jenkins, Stash, Artifactory, and Terraform.\n, • Experience with AWS services such as Lambda, DynamoDB, API Gateway, SQS, EC2, S3, CloudWatch, IAM, and EKS (preferred).\n, • Automation testing experience using frameworks like Cucumber.\n, • Background in implementing microservices architecture and highly automated, scalable infrastructure.\n\n

Founding Engineer — Confidential Search \n \n New York City | Five days on-site in Manhattan \n $250,000–$500,000 base + up to 2% equity \n Full-time | No visa sponsorship available \n \n Right, the important bit first. \n \n This isn’t one of those “Founding Engineer” jobs where you’ll arrive as employee 47 and spend your first month sitting in planning meetings. \n \n You’ll be the first engineering hire, joining two founders in a small, seriously profitable business that has gone from zero to significant eight-figure revenue in under a year — without raising outside funding. \n \n The company is building a real-time pricing and decisioning platform for a fast-moving consumer marketplace. The engineering problems look a lot like electronic trading: huge amounts of changing market data, automated bidding, live inventory and decisions where the financial impact shows up almost immediately. \n \n You’ll sit beside the founders in the office and own the core technology behind it. \n \n What you’ll actually be doing \n \n • Building and owning the pricing engine, bidding infrastructure and data systems that power the platform \n • Turning AI and model research into production systems that run continuously \n • Building proper experimentation and A/B testing frameworks around pricing decisions \n • Improving the speed, throughput and reliability of the bidding systems \n • Creating AI-powered tooling for triage, production failures and model-drift detection \n • Making the big early architecture calls and setting the engineering standard as the team grows \n • Getting very close to the commercial side of the business — what you ship can affect revenue within hours \n \n The non-negotiables \n \n • You have 3–10 years of professional software engineering experience \n • You have genuine 0→1 experience. You’ve personally taken an ambiguous product or technically difficult system from an idea into production — ideally as a founder, founding engineer or one of the first engineers \n • You’ve worked somewhere with a genuinely high engineering bar, whether that’s a top technology company or a smaller team solving very hard problems \n • You’ve designed, built and operated data-intensive production systems \n • You’re strong with Python, or close enough technically that moving into a Python-heavy environment won’t be an issue \n • You have proper platform, infrastructure or distributed-systems experience \n • You’re naturally good with data and comfortable making decisions when the information is incomplete, noisy or moving quickly \n • AI is already part of how you build. You’re using LLMs, agents and modern developer tooling in real work, not just playing around with them at the weekend \n • Your career shows progression, ownership and things you have actually shipped \n • You’re comfortable disagreeing with smart people, backing your opinion and changing it when the evidence proves you wrong \n • You’re still a very hands-on engineer. This isn’t a people-management or operations role \n • You can work on-site in Manhattan five days a week \n • You already have unrestricted US work authorisation. Unfortunately, sponsorship isn’t available \n \n You’ll probably be especially interesting if \n \n • You’ve founded something yourself or joined very early and helped it achieve real commercial traction \n • You’ve built systems around pricing, trading, marketplaces, bidding or optimisation \n • You’ve worked on production AI, model evaluation, automated operations or experimentation \n • You’re interested in markets, pricing or trading systems \n • You have a strong computer science background \n \n Why it’s worth a look \n \n You’ll be joining a tiny, profitable team with no investors breathing down its neck and no layers of approval. There’s a lot still to build, the problems are properly difficult and the upside is real. \n \n You won’t be handed a polished roadmap. You’ll work things out with the founders, challenge them when needed and take full ownership of what gets built. \n \n The base salary is $250,000–$500,000, depending on experience and the level of impact you can have, with up to 2% equity on top. \n \n The process \n \n 1. A 30-minute chat with one of the founders \n 1. A one-hour technical interview with the technical co-founder \n 1. A take-home exercise \n 1. A presentation of your work to the team \n 1. A final on-site meeting \n \n If it’s a strong fit on both sides, the whole thing can move from first chat to offer inside two weeks. \n \n When you apply, make it easy to see what you personally owned, what you built from 0→1 and what happened as a result. A list of technologies won’t tell the story — the interesting bit is what you actually built.

We are seeking a hands-on Senior AI Native Engineer to design, build, and deliver production-grade AI agents, LLM-integrated applications, and developer productivity tooling on AWS. \n The ideal candidate is an experienced software engineer who remains actively involved in coding and uses GitHub Copilot and/or Claude Code CLI as part of their day-to-day development workflow. This role requires proven experience taking agentic AI or LLM-based solutions beyond proof-of-concept into production environments, with strong foundations in cloud-native engineering, Microservices, APIs, and DevOps. \n \n Basic Qualifications – Must Have \n • 7+ years of experience in hands-on software engineering, including Microservices, APIs, cloud-native applications, and enterprise software development. \n • 3+ years of strong hands-on experience with AWS, DevOps/CI-CD, and cloud-native architecture. \n • Proven hands-on experience personally building and deploying an AI agent, LLM integration, or agentic workflow into a production environment. \n • Current hands-on development experience, with active individual-contributor coding experience within the last 6 months. \n • Demonstrated day-to-day use of GitHub Copilot and/or Claude Code CLI for software development, with the ability to explain specific real-world use cases. \n \n Technical Skills \n • Agentic AI: AI Agents, Agentic Workflows, Tool Calling, Multi-Agent Systems \n • Agent Frameworks: LangGraph, LangChain, CrewAI, AutoGen, Strands, Bedrock Agents \n • Protocols: Model Context Protocol (MCP) \n • AI/LLM Platforms: AWS Bedrock, Anthropic APIs, OpenAI APIs, Azure AI Foundry \n • Cloud: AWS \n • Architecture: Microservices, REST APIs, Event-Driven Architecture, Cloud-Native Applications \n • AI Coding Tools: GitHub Copilot, Claude Code CLI \n • DevOps: Git, CI/CD, automated testing and deployment \n • LLM Observability: Langfuse, LangSmith, Braintrust, Weights & Biases \n • AI Patterns: RAG, Embeddings, Vector Search, LLM Evaluation, Guardrails

Project Description: \n\n • We are looking for a C++ engineer to design and build high performance, low latency applications that process large volumes of real time data. You will work on systems where microseconds and throughput matter, optimizing every layer from algorithms and data structures to networking and OS interaction.\n, • Compensation 110000-140000 USD Gross per year based on the interview process results.\n, • Responsibilities:\n, • • Design, implement, and maintain high performance C++ services handling high message rates and low latency workloads.\n, • • Optimize existing components for latency, throughput, and CPU/memory efficiency.\n, • • Develop and tune networking, messaging, and I/O layers to handle large data volumes reliably.\n, • • Profile and debug performance issues at application, OS, and network levels.\n, • • Collaborate with quantitative, trading, and infrastructure teams (or analogous business/tech teams) to translate requirements into robust technical solutions.\n, • • Write clean, production quality code with appropriate tests and documentation.\n, • • Participate in code reviews, design discussions, and continuous improvement of engineering practices.\n\n \n Mandatory Skills Description: \n\n • • Strong proficiency in modern C++ (C++17/20 or later)\n, • • Solid understanding of concurrency and synchronization (lock free / low lock patterns, atomics, memory models, etc.).\n, • • Proven experience building performance critical, real time, or low latency systems (e.g., networking, trading systems, telemetry, gaming engines, or similar).\n, • • Strong knowledge of computer science fundamentals: data structures, algorithms, memory management, and optimization.\n, • • Practical experience with Linux systems programming (sockets, epoll/select, threads, memory management, CPU affinity, etc.).\n, • • Experience using profiling, benchmarking, and performance analysis tools (e.g., perf, valgrind, flame graphs, CPU/memory profilers).\n, • • Proficiency with version control (Git) and standard build systems (CMake, Ninja, etc.).\n, • • Excellent problem-solving skills and attention to detail; ability to work in a fast-paced environment.\n\n \n Nice-to-Have Skills Description: \n\n • • Experience with kernel bypass or user space networking technologies (e.g., DPDK, RDMA, VMA, Solarflare/OpenOnload) - helpful but not required.\n, • • Experience in financial markets, market data distribution, order routing, or exchange connectivity.\n, • • Familiarity with common market data protocols (e.g., FIX, MDP, ITCH, proprietary exchange feeds) is a plus.\n, • • Experience with multicast, low latency networking, and clock synchronization (e.g., PTP).\n, • • Exposure to hardware aware optimization (NUMA, cache optimization, vectorization/SIMD, CPU pinning).\n, • • Experience with monitoring/telemetry for high performance systems (latency histograms, throughput metrics, SLAs).\n, • • Familiarity with scripting languages (e.g., Python, Bash) for tooling and automation.\n\n

Role: Applied AI Engineer \n Location: New York, NY \n Onsite: 4-5 days \n Duration: 12 months \n Interview Process: \n\n • 1st: In-person\n, • 2nd: In-Person\n\n \n Must Have: \n\n • Strong background within Machine Learning\n, • Everything withing AI starts here\n, • Strong within Python (NOT looking for a software developer who has learned how to use models. Instead, looking for a core math background, machine learning, data model extraction and/or trading models.\n, • Pytorch\n, • Langchain\n, • Core AI Tools\n, • Document Extraction Experience and comfortable enhancing the model to produce better extraction\n, • RAG experience is a MUST\n, • Agentic Workflows Exp\n, • Ability to orchestrate workflows of a system. Someone who has applied their knowledge into apply agentc workflows - move through steps from beginning to end. Do transformation on it and produce a result\n, • Llm OPS\n, • NOT LOOKING FOR A SOFTWARE DEV WHO learned how to use models\n, • Building production systems and not just trying to learn something\n, • Someone who has applied knowledge into how EFFECTIVELY they can apply agentic workflows\n, • Must have professional experience working with a LIVE system, opposed to someone doing this recreationally\n, • Financial Services is a HUGE plus\n\n \n Plus: \n\n • Engineering Exp front to back\n, • Build workflows, examine systems, suggest solutions to it using data flows and gen AI, etc\n\n Fixed Income or Institutional Lending domain experience. \n • Experience working in regulated environments with strong audit and control requirements. \n • Familiarity with enterprise security, data governance, and entitlement models. \n • Experience designing reusable internal platforms or shared developer tooling. \n • Frontend experience is beneficial (Angular or React) \n \n D2D; \n • Design and evolve reusable GenAI workflows used across Lending business lines. \n • Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review. \n • Build AI-powered assistants embedded in Lending systems using agentic workflows. \n • Deliver automated content and deck generation workflows for reporting and approvals. \n • Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy. \n • Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring. \n • Design and implement controls for entitlements, PII handling within open-source models in a regulated environment. \n • In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across Lending. \n \n Misc: \n\n • They do not have this type of candidate on team today - they need this candidate to come in and be a SME on the team and be confident enough to bring their own two sense into the role.\n, • AI Platform is being built from scratch\n, • Need this candidate to bring knowledge of how to chain workflows and how to enhance extractions\n, • Stakeholders\n, • Strats (heavy math background) + Operations Users + Business Users\n, • Current Volume of Documents: Lending volume is Massive\n, • Docs can go from 1 page to 300+ pages (PDFs)\n\n \n Redflags: \n\n • Developer who simply is using AI\n\n \n Ideal Candidate: \n\n • Applied AI SME - how can come in and say " THIs is how it needs to be done, this is what I will need to do it, this is my timeline, etc."\n, • Practitioner is someone who not just someone giving out straight answer.\n\n

Job title: Senior Java Web Engineer \n Location: New York, NY 10005 \n • 1st Preference: New York City, NY \n • 2nd Preference: Massachusetts, Fort Mill, South Carolina, Raleigh, North Carolina, Washington DC \n \n Work Arrangement: Hybrid \n Employment Type: Contract \n Compensation: $45 per hour W2 \n Desired Start Date: 09/19/2026 \n \n About the Role: \n \n We are seeking an experienced [Senior Java Web Engineer] to join our team. The successful candidate will be responsible for the job responsibilities as listed below and will work closely with [team/stakeholders] to deliver high-quality solutions. \n \n Key Responsibilities: \n · Contributes to design, development, and implementation of backend services and web applications. \n · Writes clean, maintainable, and well-tested code following established engineering practices. \n · Participates in technical design discussions and collaborates with senior engineers and architects. \n · Works closely with frontend developers to integrate backend services with UI components. \n · Supports troubleshooting, debugging, and performance optimization of applications. \n · Breaks down user stories into technical tasks and delivers within agreed timelines. \n · Collaborates effectively in Agile teams with product owners, QA, and other developers. \n · Maintains and improves existing systems while ensuring stability and reliability. \n · Builds positive relationships within the team and contributes to a collaborative environment. \n · Communicates technical concepts clearly to both technical and non-technical stakeholders. \n · Continuously develops technical expertise and stays up to date with modern technologies and frameworks. \n \n Required Qualifications: [4-8]+ years of professional experience in [Java 21, React (version 17), Spring Boot 3.x ]. \n \n Essential skills: \n · Strong Java fundamentals (Java 21 preferred) including core concepts (collections, concurrency, memory management). \n · Solid experience with Spring Framework (Spring 4+) and Spring Boot 3.x. \n · Experience building and consuming REST APIs. \n · Good knowledge of React (version 17) and integration with backend services. \n · Strong understanding of web application architecture and client-server communication. \n · Experience with SQL and relational databases (e.g. PostgreSQL). \n · Proficiency with version control (Git) and build tools (Maven/Gradle). \n · Strong focus on clean code, unit testing, and code reviews. \n · Familiar with Agile development practices. \n · Comfortable working in Linux/Unix environments. \n · 4–8+ years of software engineering experience. \n \n Other desirable skills: \n · Experience with JSF / JSP applications and legacy UI technologies. \n · Familiarity with modern frontend practices and component-based architectures. \n · Experience with CI/CD pipelines and testing practices. \n · Exposure to Docker / containerization. \n · Basic understanding of distributed systems. \n · Familiarity with Spring ecosystem tooling. \n · Knowledge of financial systems or trading platforms is a plus. \n \n Educational background: \n · BS/MS in Computer Science or equivalent software engineering qualification. \n \n Interviews: \n There are three rounds of interview to select the candidate \n Round 1: Technical discussion \n Round 2: Live coding test by client \n Round 3: Technical discussion with client (Face to face for New York location candidates, Virtual for other location candidates) \n \n Work Authorization: Applicants must be legally authorized to work in the United States. \n \n Equal Employment Opportunity \n \n Themesoft Inc is an Equal Employment Opportunity employer. We consider qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local law. \n

\n \n Job Title: ELK STACK Engineer. \n Location: New York, NY \n Duration: 6 Months initially (extension possible) \n Job Type: Temporary Assignment \n Work Type: Hybrid (2 days onsite per week) \n Pay Rate: $50.00 - $57.00/Hr \n \n Overview: \n \n TekWissen is a global workforce management provider headquartered in Ann Arbor, Michigan that offers strategic talent solutions to our clients world-wide. Our client is a global professional services firm specializing in digital transformation, business process management (BPM), analytics, and AI-driven solutions. The company partners with organizations to improve efficiency, transform operations, and drive business outcomes through a combination of process expertise, technology, and data insight. \n \n Job Description: \n \n Role Summary \n\n • We’re seeking a Search Platform Engineer with strong ELK stack expertise.\n, • The role focuses on Solr platform support across non-prod and prod environments and ElasticSearch PoCs, ensuring performance, reliability, and secure operations.\n\n Key Responsibilities \n Apache Solr (Primary) \n\n • Lead Solr administration across non-prod and prod environments.\n, • Operate SolrCloud (ZooKeeper, shards, replicas, leader election).\n, • Perform deep JVM tuning (heap/off-heap, GC, threads, caches).\n, • Diagnose and resolve search performance issues (CPU, GC, latency, throughput, memory leaks).\n, • Optimize high-volume indexing (commit strategies, merge policies).\n, • Enforce security and HA (TLS, RBAC, audits, zero-downtime upgrades).\n\n ELK Stack (Secondary) \n\n • Design and run Elasticsearch clusters for PoCs and production.\n, • Tune mappings, shards, JVM, and query DSL.\n, • Secure Elasticsearch using TLS and role-based access control.\n, • Implement observability and alerting (e.g., Prometheus, Grafana, Elastic).\n, • Platform Operations\n, • Execute capacity planning, benchmarking, and RCAs for search platforms.\n, • Ensure documentation, runbooks, and operational best practices.\n\n Lucidworks Fusion (Preferred) \n\n • Install, configure, and support Fusion (on-prem/cloud).\n, • Manage custom Fusion JARs, patches, and vendor-led upgrades.\n, • Build and tune ingestion and query pipelines.\n, • Troubleshoot Fusion/Spark and connector failures.\n\n Required Skills (Must-Have) \n\n • hands-on Apache Solr administration experience.\n, • Deep expertise with SolrCloud operations and JVM tuning.\n, • Strong troubleshooting skills for performance, indexing, and query optimization.\n, • Solid understanding of TLS, RBAC, HA, and zero-downtime upgrades.\n, • Experience supporting Lucidworks Fusion (installation, pipelines, upgrades).\n, • Secondary/Optional Skills (Good to Have)\n, • ELK stack administration: Elasticsearch (PoCs & production), Logstash/Kibana exposure.\n, • Observability tooling: Prometheus, Grafana, Elastic.\n, • Spark connectors and ingestion pipeline tuning.\n\n \n TekWissen® Group is an equal opportunity employer supporting workforce diversity.

About the Company \n We're partnering with a fast-growing AI infrastructure startup that's building the security, governance, and observability platform for enterprise AI. Backed by leading venture investors, the company is helping organizations securely deploy AI agents, tools, and workflows at scale. \n \n About the Role \n We're looking for a Forward Deployed Engineer to own the technical side of customer implementations. This is a unique opportunity to combine software engineering, solutions architecture, and customer-facing consulting as you help enterprise customers successfully deploy cutting-edge AI infrastructure. \n \n Responsibilities \n\n • Own technical GTM of POCs and customer implementations\n, • Run pre-sales technical deep dives, demos, and architecture discussions\n, • Troubleshoot integrations across customer environments (IdPs, security tooling, infrastructure)\n, • Build one-off solutions and custom configurations for enterprise customers\n, • Be the technical expert in the room during sales cycles, able to handle stump questions from senior engineers\n\n \n Qualifications \n\n • 4+ years of software engineering, solutions engineering, or technical consulting experience\n, • Strong technical background with experience in enterprise infrastructure, security, or AI platforms\n, • Expert of Model Context Protocol (MCP) with hands-on experience working with MCP-based tools, integrations, or infrastructure\n, • Preferred Computer Science degree\n\n \n Bonus Qualifications \n\n • Shipped production code at some point in your career\n, • Experience with enterprise infrastructure, identity systems, or security tooling\n, • Built your own side projects or have founder experience\n\n \n If you're interested, please apply now or contact Ellena Yeo at ellena.yeo@talentinternational.com.

Company Description Meridian brings context-aware AI agents to industries that have traditionally been overlooked in technology adoption such as supply chain, manufacturing, staffing and more. The company works closely with sector experts to automate operations, enhance decision-making, and unlock new efficiencies through applied AI. Meridian is backed by leading investors, including Sunflower Capital, Pear VC, SV Angel, and angels from Anthropic. Team members join a fast-moving environment where they can shape products from the ground up and see their work deployed directly in critical industry workflows. \n \n Role Description As a Forward Deployed Engineer at Meridian, you will work on-site with customers and internal teams in New York, NY to design, build, and deploy Agents. This full-time role involves translating complex real-world workflows into technical requirements, implementing back-end services and integrations, and iterating quickly based on user feedback. You will collaborate with customers to collect context, build agents and ensure robust, secure, and scalable deployments. Day-to-day responsibilities include talking to customers, writing production-quality code, managing data pipelines, debugging and optimizing systems in live environments, and documenting solutions for long-term maintainability. You will also contribute to best practices, help improve internal tooling, and support go-live and post-deployment operations. \n \n Qualifications \n\n • Strong foundation in Computer Science, including algorithms, data structures, and systems concepts.\n, • Hands-on experience with Software Development and Programming in Python.\n, • Proficiency in Back-End Development, including APIs, databases, and distributed services.\n, • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.\n, • Experience deploying and supporting software in production environments, ideally with cloud platforms (e.g., AWS, GCP, or Azure).\n, • Comfort working directly with non-technical stakeholders, understanding their needs, and translating them into technical solutions.\n, • Strong problem-solving skills, curiosity about applied AI, and willingness to work on-site with customers in New York, NY.\n, • Familiarity with data pipelines, ML/AI systems, or analytics tools is a plus.\n, • Ability to thrive in a fast-paced, collaborative startup environment and handle responsibility for end-to-end project delivery.\n

Hinge is the dating app designed to be deleted In today's digital world, finding genuine relationships is tougher than ever. At Hinge, we’re on a mission to inspire intimate connection to create a less lonely world. We’re obsessed with understanding our users’ behaviors to help them find love, and our success is defined by one simple metric– setting up great dates. With millions of users across the globe, we’ve become the most trusted way to find a relationship, for all.\n \n About The Role As a Senior Data Engineer at Hinge, you will create essential data processes and contribute to components of a modern data pipeline that will be the foundation of Hinge’s decision-making ability. The systems you help create, the problems you help solve, and the support of our analytical minds, will be pivotal to the success of Hinge. Your work will enable the organization to make data-driven decisions and drive improvements, which will affect the love lives of millions of people.\n \n \nAs a Senior Data Engineer on the team, you will be improving core functionality and implementing critical pipelines that will not only aid the Data Engineering team but also the rest of the organization. You will be working on an actual big data architecture while concentrating on real-world problems.\n \n Responsibilities \n\n • Work with our data teams to ensure data is flowing accurately through data creation to our presentation layers.\n, • Improve our Data Engineering stack through containerization, data modeling, developing our ETL pipelines, and more.\n, • Use your expertise in data modeling to design, build, and maintain our analytics data warehouse, which provides clean, accurate, and robust data sets that can be leveraged for reporting, analytics, and machine learning initiatives.\n, • Work with stakeholders and translate their needs and expectations into action items and deliverables.\n, • Continue to learn more about the Data Engineering discipline, utilize that knowledge in your deliverables, and identify opportunities to enhance our pipelines.\n, • Participate in our on-call rotation to ensure system reliability, promptly addressing issues to ensure smooth operations. \nWhat We're Looking For \n\n • 5+ years of professional/industry experience\n, • Proficient in Python, SQL, DevOps, and databases.\n, • 5+ years of professional/industry experience.\n, • Experience delivering data products from conception to delivery and with the infrastructure that supports their underlying processes.\n, • Experience modeling data sets for different types of sources and business processes.\n, • Passionate about designing elegant data infrastructure, tooling, and pipelines.\n, • Familiarity with our stack: Kubernetes, Docker, Terraform, Kafka, Airflow, dbt, Looker, AWS technologies (S3, Redshift), GCP technologies (Dataflow, BigQuery). and CI/CD technologies (CircleCI), Spark, Databricks \nAs a Member Of Our Team, You’ll Enjoy 401(k) Matching: We match 100% of the first 10% of pre-tax 401(k) contributions you make, up to a maximum of $10,000 per year.\n \n Professional Growth: Get an annual Learning & Development stipend once you’ve been with us for three months. You also get free access to Udemy, an online learning and teaching marketplace with over 6000 courses, starting your first day.\n \n Parental Leave & Planning: When you become a new parent, you’re eligible for 100% paid parental leave (20 paid weeks for both birth and non-birth parents.)\n \n Fertility Support: You’ll get easy access to fertility care through Carrot, from basic treatments to fertility preservation. We also provide a stipend towards fertility preservation. You and your spouse/domestic partner are both eligible.\n \n Date Stipend: All Hinge employees receive a $100 monthly stipend for epic dates– Romantic or otherwise. Hinge Premium is also free for employees and their loved ones.\n \n ERGs: We have eight Employee Resource Groups (ERGs)—Asian, Unapologetic, Disability, LGBTQIA+, Raices, Women/Nonbinary, Parents —that hold regular meetings, host events, and provide dedicated support to the organization & its community.\n \n At Hinge, our core values are… Authenticity: We share, never hide, our words, actions and intentions.\n \n Courage: We embrace lofty goals and tough challenges.\n \n Empathy: We deeply consider the perspective of others.\n \n Diversity inspires innovation Hinge is an equal-opportunity employer. We value diversity at our company and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We believe success is created by a diverse workforce of individuals with different ideas, strengths, interests, and cultural backgrounds.\n \n If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please let your Talent Acquisition partner know. #Hinge Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York City. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

We are seeking a Senior Product Engineer to join a fast-growing technology company building next-generation developer tools and AI-powered products. \n \n This role is designed for a senior, hands-on full-stack engineer who has built products from the ground up in a startup or high-growth environment. You will work closely with technical founders and other experienced engineers to shape product direction, make important architectural decisions, and take new products from initial concept through launch and customer adoption. \n \n The team moves quickly and gives engineers significant ownership. This is an opportunity to build net-new products rather than maintain an established roadmap or work within a narrowly defined engineering function. \n \n Candidates must be authorized to work in the United States without current or future visa sponsorship \n \n What You’ll Do \n\n • Own complete product surfaces from early ideation and systems design through development, launch, customer feedback, and iteration.\n, • Build and evolve developer tools and AI-powered product experiences used by engineers.\n, • Work across user interfaces, backend services, APIs, and supporting infrastructure.\n, • Partner directly with technical founders to formulate product ideas, validate them, and bring them to market quickly.\n, • Make meaningful architectural and systems-design decisions across the full stack.\n, • Prototype and ship AI-powered features, including natural-language interfaces, automation, agent-based workflows, and developer productivity tools.\n, • Build polished, high-performance product experiences across analytics, observability, debugging, and agent platforms.\n\n \n Required Qualifications \n\n • 7+ years of relevant, hands-on full-stack product engineering experience.\n, • Proven experience personally designing, building, and launching a meaningful product or major product surface from 0 to 1.\n, • Experience working in a startup, scale-up, or high-growth environment with significant autonomy and ownership.\n, • Strong full-stack engineering ability across frontend and backend development.\n, • Strong, recent experience with React, TypeScript, and modern frontend development.\n, • Backend engineering depth and experience making systems-design and architecture decisions.\n, • Experience building products used by developers, engineers, or other technical users.\n, • Experience with APIs, SDKs, developer platforms, or developer-facing tooling.\n, • Experience at a developer tools or infrastructure startup building products for engineers.\n, • Experience shipping applied AI or LLM-powered features, or compelling examples of using coding agents or agentic tools to materially improve your engineering workflow.\n, • Demonstrated ownership of product decisions from ideation through launch and iteration.\n, • Ability to move quickly, work independently, and make sound decisions in ambiguous environments.\n, • Strong product judgment and an understanding of how technical decisions affect the user experience.\n\n \n This Role May Not Be the Best Fit If \n\n • Your experience has been primarily within large, highly structured organizations without meaningful startup or high-growth experience.\n, • Your background is primarily DevOps, SRE, infrastructure, or platform operations without substantial product ownership.\n, • Your experience is limited to either frontend or backend development rather than full-stack product engineering.\n, • You have not personally taken a meaningful product from idea to production.\n, • You prefer remote or hybrid work.\n, • You require current or future visa sponsorship.\n\n \n Technical Environment \n The engineering environment includes technologies and concepts such as: \n\n • React\n, • TypeScript\n, • Go\n, • Firecracker\n, • GitHub Actions\n, • AI and large language models\n, • Claude\n, • APIs and SDKs\n, • CI/CD\n, • Developer tooling\n, • Full-stack development\n, • Systems design\n\n Not every technology listed above is required. The strongest emphasis is on React and modern frontend development, backend depth, systems design, developer-facing products, and meaningful applied AI or agentic engineering experience. \n \n Why Join \n\n • Build products that do not yet exist rather than maintain someone else’s roadmap.\n, • Own products from initial idea through daily customer use.\n, • Help expand an established developer infrastructure platform into AI-powered developer tools, agent infrastructure, and coding workflows.\n, • Join a well-funded company experiencing significant revenue growth and serving thousands of businesses.\n, • Work within a small, highly technical team with minimal management layers.\n, • Collaborate directly with technical founders.\n, • Make product and architecture decisions that will shape the platform for years.\n, • Work in an engineering culture that strongly embraces AI-native software development.\n, • Receive a competitive base salary and equity package.\n

Senior Data Engineer — Contract \n Location: Hybrid — 3 days/week onsite in Newark, NJ \n \n About the Role \n Join a major investment firm as a Senior AWS Data Engineer supporting enterprise data platform initiatives. This role focuses on building scalable data pipelines, CI/CD automation, and end-to-end data solutions across the AWS ecosystem. Experience with Informatica (data catalogue, marketplace, data lineage, data quality), Denodo, and/or Ataccama is a strong plus. \n \n Qualifications \n\n • Bachelor's degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience\n, • 8+ years of experience as a Data Engineer on the AWS stack, including DevOps tooling\n, • AWS Solutions Architect or AWS Developer Certification required\n, • Strong hands-on experience with AWS services, including:\n, • CloudFormation, S3, Athena, Glue, Glue DataBrew, EMR/Spark\n, • RDS, Redshift, DynamoDB, Lambda, Step Functions\n, • IAM, KMS, SM, EventBridge, EC2, SQS, SNS\n, • LakeFormation, CloudWatch, CloudTrail, DataSync, DMS\n, • Experience implementing high-velocity streaming solutions using Amazon Kinesis, AWS Managed Airflow, and AWS Managed Kafka (preferred)\n, • Proven experience building AWS data lake/data warehouse solutions\n, • Skilled in designing, developing, and implementing data ingestion pipelines on AWS\n, • Knowledge of ETL/ELT implementation for data solutions\n, • Experience delivering end-to-end data solutions: ingest, storage, integration, processing, and access\n, • Familiarity implementing RBAC strategies using AWS IAM and Redshift RBAC model\n, • Experience building and implementing CI/CD pipelines using CloudFormation and Jenkins\n, • Strong programming skills in Python, Shell scripting, and SQL\n, • Experience with SQL stored procedures for data analysis\n, • Experience building automated pipelines to ingest data from relational databases, file systems, and NAS shares into AWS RDS, Aurora, and Redshift\n, • Experience building automated pipelines to ingest data from REST APIs into AWS S3 and relational databases\n, • Solid DevOps background, including:\n, • Bitbucket (source code management)\n, • Python, Shell, Groovy scripting\n, • API deployment for tooling integration\n, • Jenkins and CloudBees (Pipeline as Code, Shared Libraries)\n, • SonarQube, Artifactory, and similar DevOps tools\n, • Maven, MS Build, Gradle\n, • Docker\n, • Jira and Confluence\n, • Infrastructure as Code via CloudFormation\n, • Experience creating Jenkins CI pipelines integrating Sonar/security scans and test automation\n, • Ability to accurately document exceptions, issues, action plans, meeting minutes, and lessons learned\n\n \n Responsibilities \n\n • Design, build, and maintain efficient, reusable, and reliable code\n, • Ensure optimal performance and quality of high-scale data applications and services\n, • Participate in system design discussions\n, • Independently perform hands-on development and unit testing\n, • Collaborate with the development team to integrate components into the enterprise data platform\n, • Work cross-functionally with product, QE/QA, and other teams throughout the full software development lifecycle\n, • Identify and resolve performance issues\n, • Stay current with emerging technologies and implementation practices\n, • Participate in code reviews to ensure standards and best practices are met\n, • Take ownership of estimating, planning, and managing tasks in an Agile environment\n, • Take shared responsibility for software quality rather than relying on separate QA teams\n, • Collaborate closely with all team members toward shared goals\n, • Engage with users as needed to clarify requirements\n\n

Founding Software Engineer \n NYC Hybrid - Manhattan Office \n Compensation: $180,000–$220,000 USD base salary + equity in the company \n \n Shields Group Search is partnering with an early-stage mental health technology company that is expanding its engineering team. \n \n About the Company \n Our client builds software and operational infrastructure for psychotherapy practices. The platform helps therapists and practice owners understand how their businesses are performing, identify what needs attention, and reduce the administrative work required to run a practice. \n The company is expanding its engineering team as it grows. \n \n The Role \n We are looking for an experienced, generalist engineer who can own a deliverable end-to-end across the stack without needing well-defined requirements or close management. \n The company is also building toward a product where AI sits at the core of how the system works, rather than being bolted on after the fact. Experience building agentic or LLM-powered features is a strong plus. \n You will own both the roadmap and execution for whatever you take on. This includes discussing problems, identifying opportunities, forming opinions, proposing features, making tradeoffs, building the product, deploying it, and operating it in production. \n \n What You’ll Work On: \n • Pulling data from EHR platforms and transforming it reliably at scale \n • Building and improving analytics, metrics, reports, and operational insights \n • Creating features such as prioritized tasks and recommended actions \n • Building “talk to your data” and other conversational, AI-native experiences \n • Building production features that rely on LLMs and agentic workflows \n • Deepening and expanding EHR integrations \n • Improving reliability, scalability, and data quality across the platform \n • Owning the AWS infrastructure behind whatever you build \n \n You will occasionally speak directly with therapists and practice owners, but this is primarily a product-building role rather than a customer-success role. \n \n How the Team Uses LLMs \n The team uses Claude Code and Codex as core engineering tools and is looking for someone with a sophisticated, high-throughput agentic workflow, not someone who uses AI assistants only occasionally. \n That might mean running many agent sessions in parallel, splitting large initiatives into independent workstreams, or building tooling around agent orchestration, review, and testing. \n At the same time, the company does not want someone who relies on LLMs for basic reasoning. You should have developed strong engineering judgment before coding agents were widely available, including understanding how systems work, catching bad assumptions, and navigating difficult technical decisions independently. \n The ideal candidate was already an excellent engineer and has used LLMs to become dramatically more effective. \n \n What We’re Looking For \n • Comfort owning a deliverable full-stack and end-to-end \n • Comfort working from loosely defined requirements without close management; this is not a role for someone who needs to be managed or a junior engineer \n • Extensive professional experience with Claude Code, Codex, or both \n • Experience coordinating complex work across multiple coding-agent sessions \n • A track record of owning and shipping substantial production products \n • Strong Python backend experience \n • Strong TypeScript and React experience \n • Experience operating production systems on AWS \n • Strong PostgreSQL and data-system fundamentals \n • Experience building production features that use LLMs, ideally agentic ones \n • The ability to work across product, backend, frontend, data, infrastructure, and operations \n • Strong written and verbal communication \n • The ability to disagree directly and constructively \n • Empathy for users and teammates \n • Comfort operating with limited guidance \n \n Technology stack: FastAPI, React, PostgreSQL, ECS, RDS, ElastiCache, EC2, Playwright, and GitHub Actions. \n \n\n • Experience with healthcare, EHRs, HIPAA, analytics products, browser automation, or custom agent tooling is useful but not required.\n, • This is an individual-contributor role with real scope and influence over the product. It may grow into technical leadership over time, but that is not a requirement to take it on.\n, • How the Team Works\n, • This is an early-stage company with aggressive goals, and the pace reflects that. It is a high-intensity environment, not a standard 9-to-5.\n, • At the same time, you will have substantial control over how you structure your day. The team cares about outcomes, communication, and ownership rather than fixed hours or performative availability.\n, • This is a high-autonomy position for someone who wants significant responsibility and influence.\n, • You will work directly with the founder and foundational engineer, alongside an engineer focused on data and integrations.\n\n \n This Role Is Not a Fit If You: \n\n • Need detailed specifications before making progress\n, • Require frequent hand-holding or close management\n, • Treat generated code as trustworthy by default\n, • Rely on LLMs to do the underlying reasoning for you\n, • Avoid direct or difficult conversations\n, • Are looking for a conventional 40-hour workweek\n\n \n Why Join \n Mental health care in the United States is understaffed and under strain. Therapists are overwhelmed, and the businesses behind them are often run on spreadsheets and guesswork. \n The company is building the infrastructure that allows psychotherapy practices to scale, see more patients, run healthier businesses, and spend less time on administrative overhead. \n It is a real, underserved problem, and the work you do will directly affect whether practices can grow and survive. \n \n Beyond the mission, you will: \n • Own meaningful, company-defining product surfaces \n • Shape both the roadmap and the architecture \n • Build on an existing product and customer foundation \n • Build AI-native features tied to real operational outcomes \n • Help define an agent-native engineering culture \n • Work directly with the founders

Company Profile: \n AppCard Inc. is a technology and marketing company headquartered in Manhattan, NY. Appcard has a powerful marketing tool that leverages data acquired at the point of sale (POS) via an advanced rewards program to create advanced retargeting campaigns that help businesses increase their bottom line. AppCard is unique in the loyalty space due to its patented technology which allows businesses to capture shopper identity and item level data in realtime from purchases made in store and online. The benefit of this is two fold: consumers benefit by receiving offers, incentives and coupons. Through a shopper’s interactions with the former AppCard’s platform records and learns shopper behavior and gives grocers the ability to make their data actionable to increase average basket size and systematically increase repeat purchases. \n \n About the role: \n We are seeking an experienced Senior Devops Engineer to design, build, and maintain our hybrid infrastructure, which spans both cloud and IOT environments. This role is hands-on and involves managing IoT devices at scale, developing tools for system deployment and monitoring, and leading modernization projects from design through production. You will collaborate with cross-functional teams to ensure the development of reliable, secure, and scalable systems, while mentoring teammates and driving best practices in infrastructure engineering. \n \n What you’ll do: \n\n • Own, design, build, and maintain infrastructure for part of our cloud-based and on-premise IOT environments, ensuring reliability, security, and scalability\n, • Develop and introduce tools to enhance the deployment, management, and monitoring of customer premise equipment, IoT devices and backend systems\n, • Manage system architecture and modernization projects, driving them from design through implementation to production operations\n, • Enhance observability and monitoring of infrastructure and IoT devices, developing both custom tooling and utilizing off the shelf offerings\n, • Implement secure connectivity solutions to ensure resilient and safe device-to-cloud communication\n, • Mentor and guide team members, sharing best practices in infrastructure, monitoring, and system design\n\n \n What you have: \n\n • 5+ years of experience in Infrastructure Engineering, SRE, or DevOps roles with strong Sys-Admin background in Linux systems\n, • Strong Linux systems and networking knowledge (docker, firewalls, load balancers, and VPNs)\n, • Solid background in monitoring, alerting, and troubleshooting large-scale distributed systems\n, • B.Sc. in Computer Science or equivalent\n, • Software development skills relating to building infrastructure (Python)\n, • Hands-on expertise with a variety of AWS services\n, • Proven ability to manage and secure hybrid (Cloud + On-Prem) infrastructure\n, • Familiarity with Infrastructure as Code (Terraform, Ansible, CDK etc.) for automation and system consistency\n, • Excellent communication skills in English; team-oriented and proactive mindset\n\n \n Preferred Qualifications: \n\n • Strong experience managing servers and/or IoT devices at scale\n, • Experience with AWS IoT offerings, such as GreenGrass v2\n, • Knowledge of best practices of secure infrastructure design\n\n \n This role is full-time from our NYC office \n Applicants must be authorized to work in the U.S. This position is not eligible for employer visa sponsorship."

Job Description Our client is an early-stage industrial software company building an AI-driven production orchestration platform for aerospace, defense, and advanced-manufacturing customers. The company has raised approximately $11M, is preparing for a Series A, employs roughly 30 people, and works with high-profile manufacturers including leaders in space and defense. You will be the first dedicated Site Reliability Engineer and own critical infrastructure end to end. This is a greenfield opportunity to architect the path from AWS to on-premises and air-gapped deployments, support customer-specific cloud environments, and improve observability and delivery systems across the platform. Requirements Design, build, scale, and operate cloud and on-premises infrastructure as the sole SRE. Architect migrations from AWS into on-premises and air-gapped environments. Bring 1-4 years of experience in cloud infrastructure, SRE, or DevOps, including containerization. End-to-end infrastructure ownership at a startup or small team is important. Experience with on-premises, hybrid cloud, restricted, or regulated deployments is strongly valued. Hands-on AWS, GCP, or Azure experience is required; Kubernetes, Docker, Terraform, Terragrunt, OpenTofu, CI/CD, GitOps, networking, and observability tooling are valuable. US citizenship or permanent residency is required. Benefits $120K-$180K base salary plus competitive equity. Full-time and on-site five days per week in Midtown Manhattan, New York City. Relocation support is available. Visa sponsorship and transfers are not available. You will have rare greenfield ownership as the first dedicated SRE at a mission-driven industrial technology company.

Job Description CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. What You'll Do: The Field Engineering organization at CoreWeave supports the clients running some of the largest AI workloads in the world. This team builds the tooling that engineers rely on to identify and diagnose customer issues faster. We work where AI and deterministic based systems meet live production infrastructure, so what we build has to be accurate, has to show its reasoning, and has to earn the trust of engineers who are the real experts solving issues. About the Role: As an AI Engineer, you'll design, build, and operate systems that engineers use during real customer incidents. You will define the right balance between deterministic and AI systems, and work with both. For AI systems, you'll own the agent logic, the retrieval behind it, the safeguards that stop it from acting on bad information, and the measurement that tells us whether it's actually helping. This is a full-ownership role: you ship your own services and stay responsible for how they behave in production. You'll work closely with the engineers who use what you build. In this role, you will: • Design and build AI agents that investigate and act on real customer issues., • Build the safeguards that make that safe: grounding model output in authoritative data, requiring human approval before consequential actions, and defining the conditions under which the system should stop., • Build and evaluate retrieval over a large body of historical support data, measured against how experienced engineers handled the same problems., • Determine the optimal balance between AI and deterministic logic., • Instrument these systems for quality, cost, and adoption, then use what you learn to decide what to build next., • Deploy and operate your own services on Kubernetes, including supporting them when something breaks., • Partner with support engineers and domain experts, including sitting in on live investigations to see where automation helps and where it gets in the way. Who You Are: • 3+ years of professional software engineering experience, with strong proficiency in Go or Python., • Experience taking an AI application from prototype to production use and supporting it afterward., • Hands-on experience with agent patterns: tool and function calling, multi-step orchestration, and handling incorrect model output., • Experience building and evaluating retrieval systems, including measuring quality against a baseline using held-out data., • Experience designing controls for automation that acts on production systems, such as approval steps, idempotency, and audit trails., • Experience diagnosing failures in LLM applications and fixing the underlying cause rather than the symptom., • Experience with observability for LLM applications, including tracing, cost, and latency., • Working knowledge of Kubernetes and experience deploying services through CI/CD., • Experience integrating with third party APIs, including authentication and secrets handling. Preferred: • Experience building conversational or chat-based interfaces for internal users., • A background in infrastructure, SRE, or technical support, and comfort reading logs and metrics from a live system., • Experience testing both deterministic and non-deterministic systems., • Experience with fine-tuning or building training datasets from production data., • Open source contributions to AI tooling or agent frameworks. Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. • You can tell the difference between the thing that's interesting and the thing that's urgent, and you'll say so out loud when they aren't the same., • You've worked with a team that already had tooling they liked, and found the integration instead of arguing for a rewrite., • You'd rather sit in on a real incident than infer how the work goes from a ticket., • Blunt feedback from the engineers using your software is the most useful thing you'll hear all week, and you don't get defensive about it. The base salary range for this role is $143,00 to $210,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment, • A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com. Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.

Job Description Tired of the inefficiencies and complexities of traditional finance? We are too. At Superstate, we create investment products that benefit from the speed, programmability, and compliance advantages of blockchain tokenization. As a Staff DevOps Engineer at Superstate, you'll be responsible for building and maintaining highly reliable, scalable infrastructure that powers our financial products. You'll architect robust systems that ensure our platforms deliver exceptional performance, availability, and security at scale. You’ll be wearing many hats across general devops, security, observability, and reliability and help lead these initiatives. What you'll do • Design and implement scalable, fault-tolerant infrastructure for our web applications and blockchain systems, • Build and maintain CI/CD pipelines, deployment automation, and infrastructure as code, • Develop comprehensive monitoring, alerting, and observability systems to ensure system reliabilityLead incident response efforts and conduct post-incident reviews to improve system resilience, • Implement security best practices across all infrastructure and deployment processes, • Collaborate with engineering teams to optimize application performance and reliability, • Establish SLIs, SLOs, and error budgets to measure and improve service reliability, • Automate operational tasks and reduce manual toil through tooling and process improvements, • Manage capacity planning and cost optimization for cloud resourcesWhat you'll bring to the team, • Bachelor's degree in Computer Science, Engineering, or related technical field, • 8+ years of professional software engineering or infrastructure experience, • Extensive experience with AWS cloud services and infrastructure management, • Extensive experience with infrastructure as code (Terraform, Pulumi), • Strong background in systems engineering, networking, and distributed systems, • Expertise in containerization and orchestration (ECS, EKS)Proficiency in languages (Java, Go, Rust, or similar) for automation and tooling, • Deep understanding of security principles and secure infrastructure practices, • Experience with high-availability systems and disaster recovery planning, • Exceptional problem-solving skills with a reliability and security focused mindsetBonus points if you have experience with these technologies, • Microservices architecture and service decomposition strategies, • Observability tools (Prometheus, Grafana, Sentry, etc.), • Database administration and optimization (PostgreSQL, Redis, AWS RDS), • AWS security services (GuardDuty, Security Hub, WAF, Shield, Config), • Cloudflare optimization and security configurations, • Github Actions workflows and deployment strategies, • Compliance automation for financial services (SOC2, ISO, PCI DSS), • Chaos engineering/resilience testing and reliability best practicesBenefits & Perks, • Competitive compensation, • Equity ownership, • Flexible vacation policy, • Paid parental leave, • Full medical, dental, and vision insurance, • Professional development and security certification budget We are an equal opportunity employer and value diversity at our company. We welcome qualified candidates of all races, creeds, genders, age, veteran status and sexuality to apply. Founded in 2023, Superstate is backed by leading investors including Distributed Global, CoinFund, Breyer Capital, Galaxy, ParaFi, 1kx, and Cumberland. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Job Description Mirage is an AI video company focused on making creation dramatically easier. Our team tackles some of the hardest creative and technical challenges in generative media. We get to rethink how people collaborate with AI that can actually do creative work with them—defining entirely new interaction paradigms for AI-native video tools. We make that possible by building multimodal agents that turn creative direction into edits, rendering engines that composite multiple layers of video and graphics, and generative video models trained from the ground up that create new media when needed. All of this comes together in Captions, our creative workspace for generating, editing, and designing video. The technology behind Captions is now available more broadly: Tesseract gives any AI agent native video-editing capabilities, while developers can integrate our models into their own products through APIs. Explore our work Captions — Our flagship creative workspace Tesseract — Our professional video engine for AI agents Research — The foundation models we build in-house Updates — The latest from Mirage TechCrunch, Forbes, Fast Company — Press Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role Mirage is seeking an ML Engineer to build and scale the systems powering our video generation models. You’ll work on novel modeling approaches, training objectives, scaling strategies, and inference optimization and efficiency to bring cutting-edge models into production. This role sits at the intersection of research and systems engineering, focusing on making advanced models faster, more efficient, and capable of ultra-low latency, real-time generation. Responsibilities Train and optimize large-scale video and multimodal models Improve efficiency across training and inference (memory, latency, cost) Implement techniques such as distillation, quantization, and pruning to aggressively accelerate diffusion and autoregressive generation Build and maintain distributed training systems Optimize GPU utilization, parallelism, and throughput Develop tooling for experimentation, evaluation, and debugging Translate research models into robust, production-ready systems Monitor and improve model performance in real-world usage What makes you a great fit BS/MS/PhD in CS, ML, or related field 2+ years of professional industry experience Strong experience in deep learning systems and infrastructure Expertise in PyTorch, CUDA, Triton, and distributed training (FSDP, etc.) Experience scaling and optimizing large models under low-latency inference constraints Strong debugging and performance profiling skills Ability to move quickly from prototype to production Benefits: Comprehensive medical, dental, and vision plans 401K with employer match Commuter Benefits Catered lunch multiple days per week Dinner stipend every night if you're working late and want a bite! Grubhub subscription Health & Wellness Perks Multiple team offsites per year with team events every month Generous PTO policy Captions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. Please note benefits apply to full time employees only. Compensation Range: $175K - $300K

Job DescriptionStaff Product Engineer Company: Blacksmith Location: New York, NY (Flatiron office, in person 5 days per week) Compensation: $280,000 - $380,000 + significant early-stage equity Employment Type: Full-time Visa Sponsorship: Visa transfers only (no new visas) About Blacksmith Blacksmith started by making CI workloads run much faster: its first product runs GitHub Actions substantially faster and cheaper on its own global fleet of bare-metal machines instead of rented cloud VMs. It now orchestrates tens of millions of Firecracker VMs a month for 3,000+ companies, schedules 100k+ vCPUs concurrently, and runs a petabyte-scale Ceph cluster it manages itself. Blacksmith reached about $10M ARR in under two years, has grown revenue more than 5x since the start of 2026, and has raised $58.5M through its Series B. The Role Blacksmith is hiring a Staff Product Engineer to set the technical direction for new products: AI-native developer tooling that does not yet exist anywhere in the industry. The role operates at the organization level, owning architecture, solving complex product problems and driving 0-to-1 initiatives. You will be a key technical authority and force multiplier: raising engineering standards, mentoring senior engineers and owning production outcomes as a hands-on technical leader. What You Will Do • Own and drive the architecture of new products, designing and building the next generation of AI-native developer tooling., • Translate business and product strategy into long-term technical roadmaps and execution plans., • Drive new products from 0 to 1., • Own production outcomes, including reliability, performance and operational excellence., • Mentor senior engineers and act as a force multiplier., • Operate in ambiguous spaces where both the problem and the solution need defining.What You Bring, • 7+ years as a full-stack engineer owning 0-to-1 product builds end to end, • Designed, built and shipped exceptional products in high-growth environments with recognized engineering teams, • Strong technical fundamentals across the stack, particularly TypeScript and React, • Set and led the technical direction of a product from an early stage to one known for exceptional customer experience, • Power user of coding agents and agentic tooling, with compelling examples, • Track record of leading through influence as an individual contributor, • Clear thinking and communication across engineers, leadership and non-technical stakeholders, • Ability to work in person in New York 5 days a weekNice to Have, • Experience at a developer tools or infrastructure startup building for engineersInterview Process Initial screen (30 min), technical interview I (45-60 min), technical interview II (2 hours), final onsite (30-45 min). Tech Stack TypeScript, React

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Civil Engineering Expert Type: Contract Compensation: $70–$80/hour Location: Remote Role Responsibilities • Construct civil engineering scenarios spanning large-scale infrastructure design cycles, multi-stakeholder permitting, and regulatory review., • Build tasks across structural design and analysis, transportation and highway engineering, water resources and environmental engineering, and geotechnical engineering., • Develop engineering scenarios using tools like AutoCAD Civil 3D, Revit, STAAD.Pro/ETABS, HEC-RAS, and enterprise project management platforms., • Apply civil engineering methodologies such as structural load analysis, geotechnical site assessment, and hydrology/hydraulic modeling to standards tracks like US: ASCE 7, ACI 318, AISC 360, AASHTO LRFD and International: Eurocodes EN 1990-1998 and ISO., • Author rubrics that distinguish authentic civil engineering judgment from generic textbook or coursework-level recall. Qualifications Must-Have • 5+ years working as a civil engineer or engineering lead., • Direct ownership of large-scale infrastructure designs, permitting processes, or construction project delivery., • Fluency in civil engineering tooling and methodologies., • Understanding of regulatory approvals, environmental review (NEPA or international equivalent), and public agency oversight. Preferred • A recognized professional engineering credential (US PE, CEng, EUR ING, or P.Eng)., • Prior rubric, engineering-training curriculum, or design documentation authorship. Application Process (Takes 20–30 mins to complete) • Upload resume, • AI interview based on your resume, • Submit form Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome, • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Software Engineer, Python — Codebase Q&A Type: Contract Compensation: $130 per task Location: Remote Role Responsibilities • Select tasks from a pre-validated pool of Python repositories, each pinned to a specific git commit and arriving with an engineering question, positive and negative rubrics, foils, and a golden solution., • Explore the repository until you genuinely understand the subsystem in question, including the relevant PR or issue history., • Rewrite the task's question so it defeats frontier coding agents while remaining well-defined and fairly answerable., • Adjust rubrics and foils so they reward correct reasoning and reject plausible-but-wrong answers., • Run the full validation loop in Studio — Check, Golden, Run, Analyze — and iterate until every stage passes., • Document your work in the task README and submit for expert review, addressing reviewer feedback on returned tasks. Qualifications Must-Have • 3+ years of professional software engineering experience, with substantial production Python., • Demonstrated ability to navigate a large, unfamiliar Python codebase and explain how it behaves at runtime., • Fluency in Python internals that matter in real systems: import machinery, descriptors and metaclasses, async and event loops, packaging, and C-extension boundaries., • Precise written English: the questions and rubrics you write are the product., • Comfortable with git at commit level, containerized environments, and command-line tooling. Preferred • Experience with web frameworks, developer tooling, type checkers, or scientific/numeric libraries is highly relevant. Compensation & Legal • Payment is per approved task; every task is reviewed by a second engineer and a super reviewer before acceptance. Application Process (Takes 20–30 mins to complete) • Submit your resume or relevant technical background to get started., • Qualified applicants may be asked to complete a brief technical assessment or provide additional information. Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome, • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Job DescriptionSenior Product Engineer Employment Type: Full-Time Location: New York City, NY Work Arrangement: On-site, 5 days per week Compensation: $200,000–$300,000 base salary, plus competitive equity About the Role We are seeking a Senior Product Engineer to join a fast-growing technology company building next-generation developer tools and AI-powered products. This role is ideal for an experienced full-stack engineer who enjoys building products from the ground up, operating in ambiguous environments, and taking true end-to-end ownership. You will work closely with company leadership and other highly technical team members to shape product direction, make key architectural decisions, and bring new ideas from concept to launch. The team moves quickly, operates with a high degree of ownership, and values engineers who can think beyond individual tickets or isolated technical tasks. What You'll Do Own complete product surfaces from early ideation and systems design through launch, customer feedback, and iteration. Build and evolve next-generation developer tools and AI-powered product experiences. Design workflows, user interfaces, backend services, and infrastructure that enable engineers to work more efficiently. Work closely with company leadership to formulate product ideas, validate them, and bring them to market quickly. Make important architectural and systems design decisions across the full stack. Prototype and iterate rapidly on AI-powered features, including natural-language interfaces, automation, and agent-based workflows. Own features across the entire development lifecycle, from prompt design and backend services to frontend implementation. Build polished, high-performance product experiences used by engineers and technical teams. Contribute to product strategy and help define how new products evolve over time. What We're Looking For 5+ years of experience in full-stack product engineering. Proven experience designing, building, and launching 0-to-1 products. Experience working in a startup, scale-up, or other high-growth environment. Demonstrated ownership of products from ideation through shipping and iteration. Strong full-stack engineering skills across frontend and backend development. Strong experience with React, TypeScript, and modern frontend development. Backend engineering experience and comfort making systems-level architectural decisions. Experience building products used by developers, engineers, or other technical users. Familiarity with APIs, SDKs, developer platforms, or developer-facing tooling. Experience with applied AI, AI-powered product features, coding agents, or agentic workflows is highly valued. Ability to move quickly, operate independently, and make sound decisions in ambiguous environments. Strong product judgment and an understanding of how technical decisions impact the end-user experience. Ideal Background Strong candidates will typically have experience in environments where engineers are expected to do more than execute against predefined requirements. This role is particularly well suited for someone who has: Built new products rather than primarily maintaining mature systems. Worked on developer tools, engineering platforms, AI products, or technical SaaS products. Operated in a fast-moving startup or scale-up environment. Taken significant ownership over both technical execution and product decisions. Worked across frontend, backend, and systems design rather than within a narrowly defined engineering function. A strong entrepreneurial mindset and comfort working with a high level of autonomy. This Role May Not Be the Best Fit If Your experience has been primarily within large, highly structured engineering organizations with limited startup or scale-up exposure. Your background is primarily DevOps, SRE, or infrastructure engineering without meaningful product ownership. You prefer highly defined requirements and narrow ownership over individual components. You have limited recent hands-on experience building and shipping full-stack products. Technical Environment The engineering environment includes technologies and concepts such as: React TypeScript Go Full-stack development AI and large language models Developer tooling APIs and SDKs Systems design Modern cloud and infrastructure technologies Interview Process The company is prepared to move quickly with strong candidates. The interview process is expected to include: Introductory conversation Technical coding interview Additional technical interview In-person onsite interview with the team Final leadership conversation focused on business alignment, product thinking, motivation, and long-term fit Additional Details Full-time position On-site in New York City, five days per week Candidates should already be authorized to work in the United States without visa sponsorship Base salary range of $200,000–$300,000 Competitive equity included

Job Description About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey. Position: Mechanical Engineering Expert Type: Contract Compensation: $70–$80/hour Location: Remote Role Responsibilities • Construct enterprise mechanical engineering scenarios for complex product design cycles, multi-stakeholder design reviews, and manufacturing or regulatory certification processes at Fortune 500 accounts., • Build tasks across Fortune 500 product design and CAD modeling, thermal/fluid systems analysis, structural and stress analysis, manufacturing process engineering, and reliability/failure analysis., • Develop engineering scenarios using tools such as SolidWorks, ANSYS, CATIA, MATLAB/Simulink, and enterprise PLM systems (Siemens Teamcenter, PTC Windchill) in Fortune 500 stacks., • Apply enterprise mechanical engineering methodologies (FEA/CFD simulation, DFM/DFA principles, Six Sigma/DFSS, GD&T standards) to produce reference design specifications, engineering analyses, and executive-level technical narratives., • Author rubrics that distinguish authentic enterprise mechanical engineering judgment from generic textbook or coursework-level recall. Qualifications Must-Have • 5+ years working as a mechanical engineer or engineering lead at a Fortune 500 industrial, automotive, aerospace, or manufacturing company (GE, Boeing, Caterpillar, Ford, Honeywell)., • Direct ownership of Fortune 500-scale product designs, manufacturing processes, or engineering certification programs., • Fluency in enterprise mechanical engineering tooling and methodologies, plus understanding of how Fortune 500 safety standards, regulatory certification (ISO, FAA, FDA), and cross-functional design governance work. Preferred • Prior rubric, engineering-training curriculum, or design documentation authorship. Application Process (Takes 20–30 mins to complete) • Upload resume, • AI interview based on your resume, • Submit form Resources & Support • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome, • For any help or support, reach out to: support@mercor.com PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Job DescriptionAbout Monstro Monstro provides the AI-powered Financial Intelligence System for regulated financial institutions. It enables banks and wealth managers to deliver continuous, personalized, governed Financial Guidance to every client, not just the top tier, across their entire financial life: saving, borrowing, investing, planning, protecting, and preparing. Meaningful Financial Guidance has only ever been available to a small portion of people. We are changing that, through the institutions people already trust. Institutions already have the relationships, the data, and the context to understand each client; Monstro turns that understanding into guidance that helps each person understand, decide, and act. For clients, that means clearer decisions, proactive support when life changes, and a better view of their financial lives. For institutions, it means deeper relationships, more clients served consistently, and more of each client's financial life managed in one place. What makes this possible is how the system is built. Governance is not an added feature; it is foundational. Every recommendation reflects the institution's own views, policies, and permissions. Every output can be audited, traced, and reversed, and client data stays under the institution's control. Generative AI is used to build and configure the system; at runtime, execution is deterministic, so every output can be explained and stood behind, not just trusted. The work We are building for a high-stakes industry where the work has real consequences. Guidance only matters if people can trust it and institutions can govern it. The challenge is to make Financial Guidance more personal and more available without making it less trusted: to build AI that institutions can audit, explain, and reverse, in a domain where being wrong carries real cost. That is what makes the problem hard, and the work meaningful. This is not a simple AI problem; it takes product judgment, technical depth, regulatory discipline, design quality, and a team that moves quickly without lowering the bar. Monstro is moving from vision to market: launching with financial institutions, growing the team, and building for the enterprise in one of the most regulated industries. You will be expected to think clearly, communicate directly, move with urgency, hold a high standard, and take responsibility for work that matters. We are an early team building something ambitious, and what you do here will shape both the product and the company. About the Role We're looking for a Staff Software Engineer to support our AI application development team at the heart of the company's mission. This is a deeply technical role with real scope: you'll architect and ship systems that power AI-driven financial analysis, build the tooling and infrastructure that domain experts rely on, and set the engineering bar for how we build AI systems responsibly in a regulated industry. You'll influence how we design agents, how we validate and govern AI output, how we scale our modeling infrastructure, and how we think about auditability and compliance. This isn't a role where AI is a thin wrapper — the intelligence layer is the product. What You'll Do • Architect and build AI agent systems — including multi-agent workflows, orchestration layers, and the infrastructure that makes them reliable and auditable in production, • Work at the edge of what's possible with modern AI — rapidly evaluating new models, tools, and development patterns, and setting the technical direction for turning the most promising capabilities into robust production systems., • Design modeling and reasoning systems that meet the correctness and explainability requirements of financial services — where every recommendation needs to be traceable and defensible, • Build internal applications and platforms (Python/React) that enable domain experts and engineers to author, validate, and deploy AI-powered analysis at scale, • Document your decisions, ensure sufficient test coverage and generate AI native artifacts to share your work with others, • Own distributed backend infrastructure: event-driven workers, job pipelines, and multi-stage processing systems that deliver AI outputs reliably under load, • Establish patterns for AI output validation and quality assurance — including automated evaluation pipelines, hallucination detection, and compliance guardrails, • Drive technical decisions across teams: schema design, API contracts, system boundaries, and service architecture, • Contribute to full stack application development, • Lead engineering initiatives across team members and cross functional partners, • Establish and promote engineering and architecture best practices and the adoption of new AI technologies and techniques, • Mentor senior engineers and raise the engineering bar across the organization What We're Looking For, • 8+ years of engineering experience, with a track record of leading complex systems from design to production., • Deep curiosity about where AI-native software is heading, with the technical judgment to separate promising new capabilities from hype and help shape how emerging approaches are adopted across the engineering organization., • Hands-on experience designing, building, and shipping production software systems using AI development tools, especially AI-powered software, • Strong software engineering skills and experience with a demonstrated track record contributing to best practices application architecture, • Python expertise — async services, type-safe code, and systems that scale, • Strong distributed systems fundamentals: event-driven architectures, message queues, job state machines, and worker patterns, • Relational database fluency and an instinct for data modeling, • Full-stack range — you can build product-quality React/TypeScript UIs when the problem calls for it, • Opinionated about how AI systems should be tested, evaluated, and monitored in production, • Experience leading technical teams or acting as a force multiplier across engineeringPreferred but not required, • Hands-on experience with AI/ML systems — agent architectures, LLM integration, model evaluation, or AI pipelines in production, • Opinionated about how AI systems should be tested, evaluated, and monitored in production, • Experience designing multi-agent systems, agentic workflows, or AI orchestration layers, • Data engineering experience developing data pipelines handling big data, • Experience contributing to cloud infrastructure using infrastructure as code, • Background in quantitative finance, financial planning, or wealth management technology, • Experience building AI systems in regulated industries (financial services, healthcare, legal) or with compliance, auditability, or explainability requirementsWhy Monstro?, • Impact: Build technology that helps millions of people make better financial decisions, through the institutions they already trust, and help define the category of Financial Intelligence., • Ownership: High trust, high ownership, high standards. You will own meaningful problems end to end from day one., • Experienced team: Work with leadership that has a track record of scaling companies from early stage to major exits., • Principles-driven culture: We move fast, because the opportunity is urgent. We communicate directly, because clarity saves time. We hold a high standard, because institutions and clients need to trust what we build., • In person, in New York: We are headquartered at The Spiral in Hudson Yards and work in the office four days a week, because our pace depends on fast collaboration., • Compensation and benefits: Competitive cash compensation and meaningful equity, plus 100% employer-paid medical, dental, and vision coverage, disability coverage, flexible PTO, paid parental leave, and catered meals. Base Compensation Range (New York City): $224,000 - $264,000 Final compensation will depend on a variety of factors, including experience, skills, internal leveling, and market conditions, and will be offered within the stated range in accordance with applicable pay transparency laws. A Note on Interviewing: We sometimes use AI note-takers to help us transcribe interview notes, so we can be more present in your interview. If you'd like to opt out of us using automatic transcribers, please note this in the free text field in your application; otherwise we'll take your application as confirmation that you're happy for us to use note-takers (whether added to video calls or in the background). Ready to Build With Us? The standard is simple: do great work, own the outcome, communicate with purpose, move with urgency, raise the level. If that sounds like you, we'd love to hear from you.

Job Description Staff / Principal Platform Engineer Location: New York City | Hybrid Department: AI Platform & Infrastructure Team Reports to: Vangie Shue - Principal Engineering Manager About AppGate AppGate secures and protects an organization’s most valuable assets with its high performance Zero Trust Network Access (ZTNA) solution and Cyber Advisory Services. AppGate ZTNA is the only direct-routed Zero Trust solution built for peak performance, superior protection and seamless interoperability. AppGate Cyber Advisory Services harden your security posture and ensure business continuity. AppGate safeguards Fortune 500 enterprises and government agencies worldwide. Learn more at appgate.com. About the Role As we expand our platform, we are standing up a new AI Platform & Infrastructure team: the engine room of AppGate’s AI strategy. This team owns the infrastructure layer that every next-generation security capability is built on, from network observability to AI-driven threat detection and the secure operation of emerging Agentic AI systems. We’re looking for a Staff or Principal Platform Engineer to build and operate the foundational platform behind AppGate’s AI products. You combine deep DevOps and cloud infrastructure expertise with hands-on experience operationalizing AI/ML systems, and you treat observability as a first-class engineering discipline. This is a rare opportunity to join a small, private, high-impact company where your work directly shapes the architecture, reliability and core platform that defines the future of security. You’ll own the platform spanning APIs, cloud and self-managed solutions and AI/ML infrastructure, and you’ll make it fast, reliable and observable at scale. This is a high-leverage, hands-on role for a senior engineer who sets technical direction and still ships. Key Responsibilities • Build the Platform: design, build and operate the cloud infrastructure, services and pipelines that AppGate’s AI and cloud products run on. Strong experience with self-managed technologies (kafka, elasticsearch) and Kubernetes are a must., • Infrastructure as Code & Deployment Orchestration: Terraform and Helm for cloud provisioning, service deployment and configuration management., • Implement Observability: instrument APIs, cloud services and AI/ML infrastructure with metrics, logging, tracing and alerting, and define SLOs and operational health metrics that teams trust., • Data Platform: real-time and batch data ingestion pipelines, feature stores and data quality., • Integrations: third-party connectors, APIs and platform integrations., • Operationalize AI/ML: build model serving and inference pipelines, experiment tracking and the MLOps tooling for deployment, versioning, drift monitoring and lifecycle management., • Engineer for reliability & automation: apply SRE practices to reduce toil, improve resilience and keep latency and uptime within target across the platform. Automate everything - deliver infrastructure-as-code, CI/CD and self-service tooling so product teams ship safely and quickly., • Set technical direction: define platform standards, architecture and best practices, and raise the engineering bar through design reviews and mentorship., • Collaborate cross-functionally: partner with data scientists, product teams and leadership to align platform investment with AppGate’s strategic vision. Required Qualifications • Experience: extensive platform, infrastructure or SRE engineering experience, with a track record of operating production systems at scale. Staff-level candidates typically bring 8+ years and Principal-level candidates 12+ years, though we hire on demonstrated impact., • DevOps depth: strong command of infrastructure-as-code (Terraform or equivalent), CI/CD, containers and orchestration (Docker, Kubernetes), and cloud platforms (AWS)., • Observability expertise: hands-on experience implementing observability across APIs, cloud services and distributed systems using tools such as Prometheus, Grafana, OpenTelemetry, the ELK stack or comparable, including SLO and error-budget practice., • Data platform skills: familiarity with real-time and batch ingestion pipelines, feature stores and data quality at production scale., • Engineering craft: fluency in a primary backend language (Python, Go or similar) and a strong bias toward automation, testing and reliable, maintainable systems., • Leadership: a record of setting technical direction, leading complex initiatives across teams, mentoring senior engineers, while still being very hands-on., • Mindset: pragmatic, rigorous and ownership-driven. You thrive in a small, fast-moving environment and enjoy building foundations others depend on. Preferred Qualifications • AI/ML infrastructure: experience building or operating model serving, inference pipelines and MLOps tooling such as MLflow, Kubeflow, SageMaker or equivalent, including model deployment, versioning and drift monitoring., • Networking & Zero Trust fundamentals: working knowledge of the network and routing layer beneath modern access solutions — TCP/IP, TLS, tunneling/overlay networks, packet routing and filtering, DNS and firewalling — and familiarity with Zero Trust Network Access (ZTNA) or adjacent domains (VPN, SDP, SASE, software-defined networking). You can reason about traffic paths, latency and throughput end-to-end, and instrument the network as a first-class observability signal. Compensation • Staff: 185k-225k base, • Principal: 215k-270k base, • We offer performance bonuses and considerable equity. AppGate is An Equal Opportunity/Affirmative Action Employer and a federal contractor subject to the Rehabilitation Act of 1973 and the Vietnam Era Veterans Readjustment Assistance Act of 1974 as amended, and their corresponding regulations. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or veteran status, age or any other federally protected class. Further, AppGate is an affirmative action employer committed to taking positive steps to employ, advance in employment and otherwise afford equal employment opportunity to protected veterans and individuals with disabilities. In furtherance of AppGate’s policy regarding affirmative action and equal employment opportunity, AppGate has developed a written affirmative action program. This program is available for review upon request by any applicant or employee during normal business hours by contacting the company’s EEO Coordinator.

Job DescriptionAbout Ode with Anthropic How do you turn a decades-old dataset into an industry-leading medical coding agent? Teach an AI receptionist to book appointments in Spanish? Automatically generate working data connectors from API docs? Build agents that write, test, and deploy their own software packages? Anthropic is defining frontier AI. Ode is the team bringing frontier AI into practice. We are a team of experienced builders who care deeply about getting complex AI systems into production, with strong conviction about what makes them succeed. As Anthropic’s services venture, we tackle the hardest, most consequential AI problems for companies with real stakes, working closely with their Applied AI and Product teams to turn frontier technology into real world impact. We're backed by Anthropic, Blackstone, Hellman & Friedman, Goldman Sachs, General Atlantic, Leonard Green & Partners, Apollo Global Management, GIC, and Sequoia Capital. We're headquartered in SF with offices in NYC, Raleigh-Durham, and Dubai. The Role This role is designed for former engineering leaders (IC or EM) or founders who are comfortable owning end-to-end technical outcomes but specifically want to continue being impactful as individual contributors and spend more time in the code. You'll work on a small, high-caliber team (2–5 engineers and a PM) building AI products for our clients. You'll set technical direction, write code, and be the person the team looks to when something is hard. You'll spend roughly 75% of your time in code and 25% working directly with clients — often their CTOs — understanding problems, walking through tradeoffs, and making sure what we’re building meets their needs. Most engineers take a decade to see this range of hard problems across this many domains. Here, you'll do it in your first year. To make this possible, we are religious about being the best company in the world to learn Applied AI engineering practices. What You Bring 8+ years of engineering experience, with deep care for the craft. You've shipped multiple complete products end-to-end and write elegant, production-ready code across multiple disciplines. Specific interest in applying software engineering fundamentals to AI systems. You care about balancing frontier model capabilities with good system design. Comfort talking with senior technical stakeholders. You navigate conversations skillfully, and care about people using what you build. High ownership mindset. You jump in without instruction, embrace a "no job too big, no job too small" mindset, and want to shape strategy and culture. Low ego, high integrity. You help others and ask for help. You hold a high bar for honesty–with yourself and your team. Our Engineering Philosophy We have a distinct approach to building AI systems: applying standard software engineering discipline to the non-deterministic world of frontier AI. We design systems around testable hypotheses, curate durable data sets, and ensure what we ship keeps working long after we've handed it over. After shipping 30+ AI products, we have strong opinions on what makes AI products succeed and how to get them into production. We think you'll find it refreshing if you've seen how most companies approach AI. How Ode Is Different A typical engineer here ships two to three products per year and learns from dozens more. You have outsized autonomy on each product — but you won't have a year to polish a single system. The upside is constant time on the frontier of models and tooling, and a muscle for AI product development that's hard to build anywhere else. Most engineers look back at this as the biggest growth period of their career. But it's possible you won't like it — we recommend using the interview process to hear what our engineers think. Our Values Overdeliver: We are writing the playbook on how to create enterprise value with LLMs, and building our reputation as the world’s best applied AI team. Overuse AI: We obsessively explore and experiment with Claude to push the frontier of applied AI and share what we learn with our teammates. Over”engineer” the Culture: We’re building a culture that attracts and retains top applied AI talent, and we stress test large decisions through the perspective of our world class builders. Location New York, NY Work Arrangement: 4 days in-person, Fridays remote Benefits Competitive Compensation Package: Attractive salary aligned with your experience and skills. 401k with Matching: Invest in your future with our company-matched retirement plan. Unlimited PTO: Take the time you need to relax and rejuvenate. Exceptional Medical, Dental, and Vision Coverage: Comprehensive health benefits to keep you and your family healthy. Health FSA: Manage out-of-pocket health expenses effectively. Commuter Benefits: Make your travel to work easier and more affordable. Life Insurance: Providing peace of mind for you and your loved ones. Team Events and Activities: Regular events to build camaraderie and a strong team spirit. Ready to join us? Compensation Range: $275K - $400K

Job DescriptionFounding Forward Deployed Engineer New York City · On-site · Full-time Compensation: $180K–$250K base + competitive equity About the Company Our client is a well-funded, seed-stage AI company building the revenue execution platform for B2B enterprises. Their product pairs LLMs with structured customer data to tell post-sales teams which accounts to prioritize, why, and what to do next, automating work that account management and customer success teams have long done by hand. They are already live with Fortune 500 customers and have meaningful contracted revenue. Founded 2025 · Small founding team · Industry: AI, B2B, Enterprise The Role As the first Forward Deployed Engineer, you will own the technical deployment of the platform into enterprise customer environments. You will sit between messy customer data warehouses and production agent workflows, turning each customer's business knowledge into verified data models that drive measurable revenue outcomes. You will work directly with the founding team and report to the CTO. What you'll be doing • Leading new customer onboardings from start to finish: scoping data access, exploring undocumented warehouses, and mapping complex schemas to business concepts like churn, expansion, and ARR, • Building and validating the semantic layer by working with customer stakeholders, reconciling conflicting definitions, and encoding them as verified SQL, • Deploying workflows and agent pipelines into customer instances, then monitoring them to make sure they deliver results, • Running 2–3 customer engagements at a time in shared channels with customer data and engineering teams (roughly a quarter of your time customer-facing, the rest hands-on data work), • Using the internal agent tooling daily and shaping how the team improves evals, validation, and the agent harness Tech stack: SQL, dbt, data warehousing, Python, LLMs, AI agents, signal engineering, eval frameworks Requirements • 2–5 years in a forward deployed, data science, or customer-facing engineering role, • A track record of personally leading technical customer deployments, including data access, schema mapping, stakeholder alignment, and demonstrating value, • Experience building and shipping production data pipelines or systems on your own, from writing the code through debugging and deployment, • Strong SQL and data warehouse skills, including working confidently in poorly documented or legacy schemas and producing output you have validated yourself, • A daily AI-first workflow: you use tools like Claude or Cursor and have built or tailored your own agent-based workflows, • Solid applied statistics sense, such as understanding distributions, seasonality, and validation design, and knowing when a result is noise, • A background along one of these paths: forward deployed, customer, or solutions engineering at a leading data or AI company; analytics engineering or data science followed by customer-facing delivery; or consulting, PE, or banking paired with a genuine CS and engineering foundation, • The confidence to hold a technical position when customers push back, while staying open to changing your mind based on evidence, • Comfort with detailed, repetitive data verification, which makes up most of the role, • A bachelor's degree in computer science, data science, statistics, or another quantitative STEM field from a top-tier university, • Based in or willing to relocate to New York City and work in the office five days a weekNice to Haves, • Experience at an early-stage startup (seed through Series B); large tech company experience is most relevant when combined with startup or founder experienceWhy Join, • Join as a founding engineer at a company that already has real enterprise traction and strong investor backing, • Above-market base salary plus meaningful equity, with flexibility for exceptional candidates, • Own the most important technical path in the business, since every customer deployment runs through this role, • Attack a large, underserved market in post-sales execution with one of the first purpose-built platforms, • Comprehensive medical, dental, and vision coverage for you and your family, parental leave, a monthly wellness stipend, daily lunches, flexible vacation, and up to $10K in relocation support for out-of-state hiresDetails, • Location: New York City, NY, • Work policy: On-site 5 days a week, • Compensation: $180,000–$250,000 + equity, • Visa sponsorship: Open to visa transfers (e.g. OPT, H-1B transfers), • Employment type: Full-time

Job Description Palona’s AI agents operate in real restaurant environments: noisy phone lines, varied accents, complex menus, interruptions, incomplete information, strict business rules, and customers who expect an immediate, natural response. Improving these systems requires more than selecting the newest model. It requires disciplined evaluation, high-quality data, modeling judgment, experimentation, and production feedback loops. We are looking for an applied AI Modeling Engineer to improve the intelligence, accuracy, safety, latency, and cost of Palona’s voice and multimodal agents. You will own problems across model selection and routing, prompting and context, fine-tuning or post-training when justified, speech and language quality, evaluation methodology, dataset development, and model behavior in production. This is a product-facing modeling role. Research depth matters, but success is measured by improvements that survive contact with production and create better guest, restaurant, and business outcomes. You will work closely with product, full-stack, infrastructure, and customer-facing engineers to move from hypothesis to experiment to reliable deployment. What you’ll own • Develop modeling and experimentation strategies for high-impact agent problems in voice, language, reasoning, ordering, multilingual behavior, and multimodal understanding., • Build rigorous offline and online evaluations that measure task completion, accuracy, safety, latency, cost, conversational quality, and business outcomes., • Create and maintain representative datasets from simulations, human annotation, production feedback, and difficult edge cases while protecting sensitive data., • Evaluate frontier and open-source models and make clear build, buy, route, prompt, fine-tune, or distill decisions., • Improve prompting, context construction, memory, tool-use policies, structured outputs, model routing, and fallback behavior., • Design fine-tuning, preference optimization, distillation, or other post-training work when it offers a measurable advantage over simpler methods., • Partner with speech and real-time engineers to improve ASR, TTS, turn-taking, interruption handling, pronunciation, multilingual behavior, and end-to-end latency., • Develop analysis tools that explain model failures, slice performance by scenario, detect regressions, and accelerate iteration., • Ship model changes with production guardrails, staged rollouts, monitoring, rollback paths, and clear quality gates., • Translate new research and model releases into concrete product opportunities and communicate tradeoffs to technical and non-technical partners., • Raise scientific and engineering standards through reproducible experiments, thoughtful reviews, and clear documentation. Requirements • 3+ years of industrial experience in relevant technical domain., • Strong machine learning foundations and hands-on experience developing or evaluating production AI systems., • Strong Python skills and experience with modern ML tooling such as PyTorch, JAX, Hugging Face, or equivalent systems., • Practical experience with LLMs, speech models, multimodal models, or agentic systems., • Ability to design reliable experiments, define useful metrics, analyze noisy results, and avoid optimizing against weak proxies., • Experience building datasets, evaluation harnesses, model services, or training and inference pipelines., • Strong software engineering judgment; your work is reproducible, tested, observable, and usable by other engineers., • Ability to connect modeling choices to product constraints including latency, cost, privacy, safety, and user experience., • Comfort operating in ambiguity and collaborating across research, engineering, product, and customer contexts., • AI-native working habits and genuine curiosity about new model capabilities and limitations. Benefits • Competitive Salary and Stock Option Plan., • Medical, dental, vision, retirement, leave, and disability benefits as applicable., • Family Leave, • Short Term & Long Term Disability, • Paid time off and company holidays., • Learning and development support.

Job DescriptionSr. Azure DevSecOps Engg. Location - NJ Need 2-3 days onsite ( Hybrid ) . Need candidates only with 12 + years experience . No H1B Transfer Candidates OR OPT/CPT This is a DevSecOps Role and not DevOps. Strong Azure Services, SAST/DAST , GitHub, Kubernetes, AKS , Terraform and Python Scripting experience is required. Our client is seeking a highly skilled DevSecOps Engineer to design, build, and maintain secure and scalable CI/CD pipelines for application and database deployments. Key Responsibilities: Design and maintain CI/CD pipelines for applications and databases using tools such as Azure DevOps, Jenkins, Smart City, GitLab CI, or GitHub Actions. Automate infrastructure provisioning and configuration management using tools like Terraform, Ansible, or Helm. Integrate automated testing frameworks (junit, Slenium etc) and code coverage tools (e.g., SonarQube etc). Embed static and dynamic security scanning tools (SAST/DAST) into pipelines. Implement and monitor database CI/CD workflows for version-controlled schema migrations. Ensure secure secrets management using Azure Key Vault. Continuously monitor pipeline performance and enforce compliance, code quality, and security policies. Collaborate with application and database developers to optimize release strategies and rollback mechanisms. Conduct incident response drills, threat modeling, and vulnerability assessments within CI/CD contexts. Document DevSecOps processes and provide training to development teams on security and best practices. Required Skills & Experience: Proven experience with DevSecOps practices and tools. Proficiency in CI/CD platforms like Azure DevOps, Smart City, GitHub Actions, GitLab CI, or Jenkins. Solid understanding of cloud platforms (Azure, ). Experience with IaC tools like Terraform, CloudFormation. Strong background in code testing frameworks and code quality tooling (JUnit, SonarQube, etc.). Hands-on with database CI/CD, schema versioning, and database migration practices. Experience with containerization (Docker) and orchestration (Kubernetes, AKS). Familiarity with secure coding principles and compliance standards. Strong scripting skills in Python, Bash. Preferred Qualifications: Certifications: Azure DevOps Engineer. Experience with monitoring and observability tools. Experience in multi-cloud or hybrid-cloud DevSecOps pipelines. Familiarity with data masking, auditing, and encryption in the database CI/CD context. Flexible work from home options available.

Job Description CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at www.coreweave.com. What You'll Do As a Cloud Security Engineer at CoreWeave, you'll drive the security related efforts related to the design, implementation, and maintenance of secure cloud environments. This role requires deep expertise You'll use your deep expertise in public cloud security principles, best practices, and cutting edge technologies to define secure baselines, enforce policies, and embed security into public cloud architectures. You'll be a champion of automation and everything-as-code. You'll more than likely draw the owl as well. • Design, implement, and maintain scalable and robust security solutions for public cloud environments, utilizing guardrails, policies, and industry-leading practices, • Define and maintain comprehensive security baseline requirements, policies, and standards for public cloud platforms (e.g., AWS, Azure, GCP), • Lead the design, implementation, and automation of security controls in public cloud environments, including primitives such as IAM, detection and monitoring, configuration management, and data protection, • Utilize everything-as-code tools such as Terraform, to automate as much toil as possible, • Collaborate effectively with cross-functional teams, such as Product Engineering, and internal security teams Investing in our people is one of our top priorities, and we value candidates who can bring their diversified experiences to our teams. Here are some qualities we've found compatible with our team. We'd love to talk about whether this aligns with your experience and interests and what you're excited to work on next. Who You Are • 5+ years of progressive experience in cloud security architecture and engineering, • Bachelor's degree in Computer Science or related field, • Deep and demonstrable understanding of public cloud platforms (e.g., GCP, AWS, Azure), • Proven experience in designing, implementing, and automating security controls in cloud environments across the entire stack, • Proficient in Go and/or Python (you can write software in one of these languages), • A track record of creating meaningful technical documentation that teammates actually want to read, • Familiarity with modern CI/CD practices and Infrastructure-as-Code tooling, especially TerraformPreferred (if applicable):, • Open-source contributions in the public cloud security space, • Experience with operationalizing CSPM tooling (like Wiz), • Strong understanding of threat modeling and secure design principles, • Strong knowledge and experience with modern container orchestration technologies Wondering if you're a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are a few qualities we've found compatible with our team. If some of this describes you, we'd love to talk. Why CoreWeave? At CoreWeave, we work hard, have fun, and move fast! We're in an exciting stage of hyper-growth that you will not want to miss out on. We're not afraid of a little chaos, and we're constantly learning. Our team cares deeply about how we build our product and how we work together, which is represented through our core values: • Be Curious at Your Core, • Act Like an Owner, • Empower Employees, • Deliver Best-in-Class Client Experiences, • Achieve More Together We support and encourage an entrepreneurial outlook and independent thinking. We foster an environment that encourages collaboration and enables the development of innovative solutions to complex problems. As we get set for takeoff, the organization's growth opportunities are constantly expanding. You will be surrounded by some of the best talent in the industry, who will want to learn from you, too. Come join us! The base salary range for this role is $165,000 to $242,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). What We Offer The range we've posted represents the typical compensation range for this role. To determine actual compensation, we review the market rate for each candidate which can include a variety of factors. These include qualifications, experience, interview performance, and location. In addition to a competitive salary, we offer a variety of benefits to support your needs. The benefits below reflect our US-based offerings for full-time employees; for roles in other locations, benefits vary and are shared during the hiring process. These include: • Medical, dental, and vision insurance - 100% paid for by CoreWeave, • Company-paid Life Insurance, • Voluntary supplemental life insurance, • Short and long-term disability insurance, • Flexible Spending Account, • Health Savings Account, • Tuition Reimbursement, • Ability to Participate in Employee Stock Purchase Program (ESPP), • Mental Wellness Benefits through Spring Health, • Family-Forming support provided by Carrot, • Paid Parental Leave, • Flexible, full-service childcare support with Kinside, • 401(k) with a generous employer match, • Flexible PTO, • Catered lunch each day in our office and data center locations, • A casual work environment, • A work culture focused on innovative disruption California Applicants California Consumer Privacy Act Equal Opportunity & Accommodations CoreWeave is an equal opportunity employer, committed to fostering an inclusive and supportive workplace. All qualified applicants and candidates will receive consideration for employment without regard to race, color, religion, sex, disability, age, sexual orientation, gender identity, national origin, veteran status, or genetic information. As part of this commitment and consistent with the Americans with Disabilities Act (ADA), CoreWeave will ensure that qualified applicants and candidates with disabilities are provided reasonable accommodations for the hiring process, unless such accommodation would cause an undue hardship. If reasonable accommodation is needed, please contact: careers@coreweave.com. Export Control Compliance This position requires access to export controlled information. To conform to U.S. Government export regulations applicable to that information, applicant must either be (A) a U.S. person, defined as a (i) U.S. citizen or national, (ii) U.S. lawful permanent resident (green card holder), (iii) refugee under 8 U.S.C. § 1157, or (iv) asylee under 8 U.S.C. § 1158, (B) eligible to access the export controlled information without a required export authorization, or (C) eligible and reasonably likely to obtain the required export authorization from the applicable U.S. government agency. CoreWeave may, for legitimate business reasons, decline to pursue any export licensing process.