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Insight Global is looking for a fully remote Azure Cloud Architect to join a large financial services institution for a contract that will go until the end of the year. This would be a fully remote position in the UK. In this role, you will work closely with business and technical stakeholders to understand customer requirements and priorities, leading architectural design sessions to deliver secure, scalable, and compliant Azure infrastructure solutions across multiple divestment projects. Targeting following skillsets: • Cloud Architect focused on Azure., • Experience with Databricks as a data management orchestration tool and Azure Data Factory, • Experience with on prem data storage., • Experience operating in highly regulated industry, e.g. Financial Services., • Experience and understanding of large-scale infrastructure deployments in enterprise-wide environments required., • Success in consultative/complex technical sales and deployment projects., • Exceptional verbal and written communication skills as well as stakeholder management experience., • Experience of working with Continuous Integration (CI), Continuous Delivery (CD) and continuous testing techniques and tools with knowledge/awareness of TerraForm., • Experience in working in a global cross functional service management team., • Industry recognized Azure cloud architect certification., • Experience dealing with IT Audit, Security and Risk.

UK Government role — candidates must be eligible for security clearance. We are seeking an experienced Site Reliability Engineer with strong Linux troubleshooting skills and deep knowledge of virtual cloud networks and access technologies. The ideal candidate will have proven experience resolving complex issues across large-scale network infrastructure and cloud services in real time. Responsibilities include diagnosing and resolving production incidents, writing Python and Bash scripts on the fly to support live troubleshooting and automation, and maintaining operational reliability across cloud networking environments. Candidates should have hands-on expertise with remote access technologies such as FastConnect, IPsec, and BGP for secure and scalable route distribution. A strong understanding of Linux system processes, memory utilisation, disk and log management, network functionality, containerisation, and the TCP/IP stack is essential. The role involves triaging and resolving Severity 1 and 2 incidents using logs, metrics, and CLI tools under pressure, including failed changes or system and process failures that directly impact customers in a 24/7 operational environment. Responsibilities • Work with the Virtual Networking team to share full-stack ownership of a collection of services and technology areas, providing operational support as part of an on-call rotation. Understand the end-to-end configuration, technical dependencies, and overall behavioural characteristics of production services. Take responsibility for the delivery of the mission-critical stack with a strong focus on security, resiliency, scalability, and performance., • Hold authority for end-to-end performance and operability. Partner with global development teams to define and implement improvements in service architecture. Clearly articulate the technical characteristics of services and technology areas, guiding development teams to engineer and deliver premier capabilities within the Oracle Cloud service portfolio., • Develop and communicate a clear understanding of the scale, capacity, security, and performance attributes and requirements of the service and technology stack. Demonstrate a solid grasp of automation and orchestration principles., • Act as the ultimate escalation point for complex or critical issues that have not yet been documented as Standard Operating Procedures (SOPs). Apply a deep understanding of service topologies and their dependencies to troubleshoot issues and define mitigations. Understand and explain the impact of product architecture decisions on distributed systems., • Exhibit professional curiosity and a desire to develop a deep technical understanding of services and technologies., • Ensure high quality, accurate and timely technical documentation of incidents, problems, changes, and standard operating procedures is maintained using tools such as Jira and Confluence, • Work is non-routine and highly complex, involving the application of advanced technical and business skills within the Virtual Networking specialisation of Oracle Cloud Infrastructure (OCI). Qualifications • Strong understanding of virtual network architecture, security, and automation, • Understanding of TCP/IP stack and routing concepts in Linux systems and networking environments. IPSEC, VPNs and BGP specifically., • Experience with containerisation technologies and orchestration platforms., • Solid understanding of Virtual Cloud Networks (VCNs) in public cloud environments., • Experience with CI/CD systems and release automation tools., • Experience in scripting languages such as Python or Shell., • Familiarity with infrastructure automation tools such as Terraform and Chef., • Possess leadership experience to ensure appropriate changes, upgrades, and enhancements are made based on the technical analysis., • Must support network segmentation (e.g., security lists, network security groups, or firewalls)., • Deep Understanding of manipulating telemetry data (traffic flows, health status) using Grafana dashboards and MQL., • Experience with major public cloud providers (e.g., Oracle Cloud Infrastructure OCI, or equivalent)., • Experience using Jira and Confluence for incident tracking, knowledge management, and ongoing technical documentatio

Data Engineer Remote UK Salary: £45,000 - £55,000 This is an exciting opportunity to step into a high-impact Data Engineering role within a fast-scaling data and machine learning environment. You will sit at the core of the engineering function, working closely with a large data science group and shaping the foundations of their internal tooling and pipelines. The Company They are a rapidly growing data and analytics organisation operating in the alternative data and machine learning space. Their platform powers KPI prediction models used by investment-focused clients, and they have built a strong engineering culture to support a substantial data science function. With significant recent investment and continued growth, they are now expanding their ETL and automation capabilities to strengthen internal workflows and infrastructure. The Role You will focus on building, maintaining, and optimising internal ETL pipelines and workflow automations that support data scientists and enable reliable, scalable reporting. Key responsibilities include: • Designing and maintaining custom ETL pipelines in a cloud-native environment., • Automating internal processes and integrations across tools and APIs., • Supporting workflow orchestration using technologies such as Airflow or AWS Step Functions., • Containerising and deploying services using Docker., • Collaborating with data scientists to streamline their data workflows., • Contributing to improvements across orchestration, tooling, and internal engineering processes. Your Skills and Experience • Strong commercial experience with Python and common data libraries., • Proven ability to build and maintain ETL pipelines., • Hands-on experience with AWS services., • Experience with Docker and containerised workflows., • Familiarity with workflow orchestration tools., • Comfortable integrating with APIs and external tooling., • A practical, delivery-focused approach with the ability to own tasks end to end. How to Apply If this sounds like your next step, please send your CV to register your interest.

Senior Software Engineer – Backend (TypeScript / Node.js) 📍 Remote (UK) 💰 Circa £150,000 This opportunity is with a growing B2B technology company building backend-heavy products used by enterprise customers in a regulated space. The platform focuses on reliability, data correctness, and operational robustness. The business is continuing to scale its engineering function and is investing in strengthening the foundations of its backend systems as both the product and customer base grow. The Role: They’re looking for a Senior Backend Software Engineer to join one of their product engineering teams, with a focus on building and running services in TypeScript / Node.js. This is a hands-on role working on core backend services that underpin the product. You’ll take ownership of meaningful technical areas, contribute to architectural decisions, and help raise engineering standards as the team grows. What You’ll Be Doing: • Building and operating backend services in TypeScript / Node.js, • Owning services end-to-end, including production support, • Working with data-heavy systems where correctness and reliability matter, • Integrating with third-party APIs and external systems, • Improving performance, observability, and resilience, • Contributing to system design and architectural decisions, • Helping set and uphold engineering best practices, and acting as a senior presence in the team What They’re Looking For • Strong backend engineering experience with TypeScript / Node.js, • Experience working with modern backend frameworks and production databases, • Familiarity with cloud-native environments (AWS or similar), containers (Docker), and orchestration (e.g. Kubernetes), • Experience operating and improving production systems, not just building features, • A quality-focused mindset and a clear understanding of what “good” looks like in backend engineering, • Comfort working in complex, evolving systems with real-world reliability requirements Industry background isn’t the priority — they’re looking for solid senior backend engineers who care about building dependable systems. Why Consider It? • A chance to work on meaningful backend problems, • Exposure to complex data flows and reliability challenges at scale, • Real influence over how systems are built, operated, and improved, • An environment that values ownership, pragmatism, and engineering quality

We are seeking a highly skilled and innovative Agentic AI Engineer to join our team and drive the development and deployment of cutting-edge generative AI solutions within the Microsoft ecosystem. This position is well-suited for candidates with a background in software engineering, data science, or machine learning who excel at developing production-grade AI applications utilizing Microsoft platforms such as M365, Copilot Studio, and Azure AI Foundry, and have at least one year of relevant experience. Strong software development background with proficiency in Python. • Experience with API development using FastAPI, Flask, or Django., • Knowledge of Docker and containerized deployments., • Hands-on experience with LLM models such as OpenAI GPTs, Claude, Gemini, LLaMA, or Mistral., • Expertise in applying prompt engineering techniques to improve model performance and reliability., • Experience in implementing robust evaluation frameworks and Responsible AI (RAI) practices., • Familiarity with Microsoft GenAI/Agentic AI ecosystem such as M365, Copilot Studio and Azure AI Foundry., • Strong understanding of software engineering principles and best practices., • Ability to work in agile environments and collaborate with cross-functional teams. You'll stand out if you also meet any of the following: • You are good at prototyping and experimenting with emerging technologies to assess feasibility and impact., • You have knowledge of vector databases, RAG architectures and their integration into enterprise systems, • You have experience with GenAI development frameworks or orchestration tools such as Semantic Kernel, AutoGen, LangGraph, LangChain, or PromptFlow., • You are familiar with core agent communication protocols, including MCP or A2A., • You are a person who loves to stay current with the latest advancements in GenAI, LLMs, and AI frameworks., • You are Microsoft Certified in Azure AI Engineer Associate or Azure AI Fundamentals. 🛠️ Qualifications • Bachelor's in computer science, data science, or a related field About Avanade: Avanade is the leading provider of innovative digital, cloud, and advisory services, industry solutions, and design-led experiences across the Microsoft ecosystem. The company was founded 25 years ago as a joint venture between Accenture and Microsoft. Back then, digital transformation, automation, and AI weren’t mainstream topics—Microsoft was primarily known for Office 365. But Avanade evolved with the times and is now the number one transformation leader within the Microsoft ecosystem. We have a team of 61,000 professionals in 26 countries. We’re a truly global company with a strong local presence— what I like to call “GLOCAL”: making global impacts on a local level.

Accelerant is seeking a Product Area Lead Architect to provide hands on, operational architectural leadership for our Insights, Analytics & Workflows product area. This role operates at a Principal level, influencing architecture and execution across multiple autonomous product teams. You will work closely with team architects, engineering managers, product managers, and Data Science teams to ensure teams move fast without fragmenting the architecture. This is not an ivory tower architecture role. It is highly collaborative, pragmatic, and operational, focused on identifying architectural gaps, managing dependencies, and enabling teams to execute confidently within a shared architectural framework. You will champion standards based architecture, leveraging web standards, open protocols, and industry conventions to build interoperable, accessible, and future proof systems. Key Responsibilities Operational Architectural Leadership • Ensure architectural alignment across product teams, partnering closely with team architects and engineering managers, • Proactively identify architectural gaps, technical debt, and quality risks; drive resolution through collaboration and influence, • Manage cross team technical dependencies to enable independent, parallel execution, • Translate architectural strategy into clear, actionable guidance that teams can apply sprint by sprint Cross Team Coordination & Alignment • Facilitate architectural discussions and resolve technical conflicts across teams through principled, pragmatic decision making, • Act as an escalation point for complex cross team technical challenges, • Ensure architectural decisions are clearly communicated, understood, and consistently applied Design and Innovation • Define and maintain architectural patterns across backend services, APIs, data platforms, and front end systems, • Design scalable, resilient systems for analytics, workflow orchestration, and intelligence features, • Guide decomposition of legacy systems into well defined services and domains, • Evaluate technologies and data stores, favoring open standards and long term maintainability, • Architect distributed systems with focus on reliability, fault tolerance, and scalability Standards & Governance • Establish API design standards ensuring consistency, discoverability, and ease of integration, • Define front end standards prioritizing web platform capabilities, progressive enhancement, and accessibility (WCAG), • Create governance frameworks that balance standardization with team autonomy, • Drive adoption of industry standards (OAuth2, OpenID Connect, OpenTelemetry, JSON:API) over proprietary alternatives Technical Leadership • Partner with engineering teams on design reviews, PR reviews, and implementation guidance, • Establish standards for cross cutting concerns: API versioning, auth, observability, error handling, and resiliency patterns, • Collaborate with platform and DevOps teams on containerization, CI/CD, and cloud native deployment, • Produce clear technical design documentation that drives alignment and knowledge sharing, • Mentor engineers and raise the overall architectural maturity of the organization GenAI, ML & AI Architecture • Architect customer facing GenAI features using LLMs, including RAG pipelines, prompt engineering frameworks, and conversational AI interfaces, • Define patterns for ML model integration: serving endpoints, API contracts, versioning, and health monitoring, • Partner with Data Science to translate models into production grade features with clear integration contracts and deployment workflows, • Establish standards for responsible AI, including evaluation criteria, privacy guardrails, and LLM output validation AI Transformation & Productivity Leadership • Scale AI driven development workflows across teams, ensuring engineers leverage AI coding tools effectively, • Guide team architects and coach senior engineers on using AI tools to enhance productivity and code quality, • Work hands on with teams to identify opportunities for AI to solve operational challenges and improve velocity Solution Evaluation & Quality Assurance • Evaluate and recommend technologies to enhance capabilities across analytics, workflow, and intelligence domains, • Ensure architectural integrity through code reviews, assessments, and continuous monitoring, • Proactively identify technical risks and devise strategies for reliability, security, and performance Technical Requirements Full Stack SaaS Architecture: • Strong proficiency in modern JavaScript/TypeScript and Node.js, • Deep knowledge of web platform fundamentals and browser native capabilities, • Experience designing and evolving well structured APIs for platform integrations Architectural & Systems Thinking: • Deep knowledge of architecture principles, design patterns, and distributed systems, • Proven ability to make pragmatic tradeoffs in complex, evolving systems, • Experience in cloud native environments, preferably AWS AI Enabled Engineering: • Demonstrated experience using AI coding tools (GitHub Copilot, Cursor, Claude, etc.), • Understanding of AI applications for development productivity and code quality improvement Qualifications • 8 to 12+ years in software engineering and architecture roles, • Proven experience operating across multiple agile teams in an architectural leadership capacity, • Track record of managing cross team dependencies and bridging architectural vision with day to day execution, • Proven ability to drive AI adoption and transformation within engineering organizations, • Excellent communication and facilitation skills with ability to align work across distributed teams, • Pragmatic, operational mindset with strong problem solving abilities, • Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Senior Data Engineer – Remote UK or Europe Are you a Senior Data Engineer who wants to join a scaling SaaS startup that is just about to close its Series A? A hospitality SaaS company are shaking up the industry, building a modern platform designed around real data. 📍 Remote in UK or Europe. You will need to be +/- 2 hours UTC 💷 £80,000 - £90,000 + Equity 🤝 Interview Process 3 stages – Interview with Founder, Interview with team members, Final Technical Interview Tech Stack: Angular, TypeScript, Liveview, Tailwind, Elixir, Node, Nest, Postgres, GraphQL, Git, Kubernetes, Websockets, AWS Today the platform already processes a large volume of transactional information and has a strong data foundation in place. • ~500GB of structured transaction data, • 100M+ transactions across multiple restaurant types, • A data platform ready to scale The next step is turning this into a high-performance analytics and data infrastructure that powers benchmarking, product insights and machine learning. That is where you come in. We are looking for a Senior Data Engineer who can design and build the analytics architecture that sits alongside the transactional platform and unlocks the value of this data. The Role: You will design and build the analytics infrastructure that powers data across the business. This includes building scalable pipelines, selecting and implementing the right warehouse architecture and ensuring analytical queries can run in seconds across hundreds of millions of records. You will work closely with engineers, data scientists and ML engineers to ensure the platform supports both product intelligence and machine learning use cases. This is a hands-on role where you will own the architecture, pipelines and performance of the analytics stack. What You Will Be Doing • Design and build a scalable analytics architecture capable of handling hundreds of millions of transactions, • Build and optimise an OLAP analytics stack separate from the transactional database, • Design and maintain ETL / ELT pipelines moving data from transactional systems into the analytics warehouse, • Ensure data integrity across 100M+ transaction records, • Optimise analytical queries to deliver sub-second or few-second performance, • Implement monitoring, alerting and testing across data pipelines, • Support data modelling and suggest improvements to existing database structures, • Manage supporting infrastructure across the data platform, • Work closely with ML engineers to support model training and inference, • Collaborate with technical and non-technical stakeholders to turn business questions into efficient data models, • Contribute to the long term data architecture strategy, • Help establish data governance, consistency and quality standards across the platform Experience We Are Looking For • Strong experience as a Senior Data Engineer, • Advanced SQL skills and strong query optimisation experience, • Experience building large scale analytics systems, • Hands-on experience with OLAP databases such as ClickHouse, Snowflake or Amazon Redshift, • Experience designing and implementing ETL pipelines from scratch, • Experience implementing caching strategies using Redis or AWS ElastiCache, • Strong knowledge of AWS infrastructure, • Ability to explain complex technical ideas to non-technical stakeholders Nice To Have • Experience with real time analytics systems, • Experience building benchmarking or BI platforms, • Experience working with very large datasets, • Familiarity with orchestration tools such as Airflow, Kafka or AWS Glue, • Knowledge of partitioning and sorting strategies for large datasets, • Experience in startup or high growth environments, • Understanding of data science concepts such as clustering or recommendation 90 Day Outcomes Within the first 90 days you will be expected to deliver clear progress on the analytics platform. This includes: • Selecting the appropriate analytics warehouse based on performance, cost and scalability, • Designing and deploying ETL / ELT pipelines ingesting data from Amazon Aurora into the analytics warehouse, • Implementing monitoring and alerting across pipelines and warehouse infrastructure, • Reducing benchmark analytics query times to under 2 seconds, • Implementing a caching layer for frequently used analytical queries, • Evaluating the current data architecture and recommending improvements to support long term scale If you’ve spent most of your career working for a large business, think about applying. You’ll need to be able to adapt, pivot and face the challenges that happen in startups. Apply or DM for more information

The Opportunity - (Fully Remote, Perm role) This is a greenfield data platform build. ___ is in the middle of a major AI transformation — a multi‐agent copilot platform (KAI) is already live in production, serving manufacturing clients globally. The AI roadmap is ambitious (agentic AI capabilities, multi‐agent orchestration, voice interfaces), and the next wave of capabilities depends on a strong data engineering foundation. A Databricks lakehouse POC is being evaluated (Unity Catalog, Delta Sharing, PrivateLink to RDS), and the team is assessing the right long‐term analytics platform strategy. This role builds the entire data engineering function from scratch — defining the architecture, tooling, and patterns that power the next generation of AI capabilities. This is an entirely forward‐looking role. While there is an active platform modernisation underway (the engineering team is migrating a .NET platform from SQL Server to PostgreSQL and containerising for Kubernetes), this role’s primary focus is building new data pipelines and analytics infrastructure, not maintaining legacy systems. That said, collaboration with the platform engineering team is important, as the data pipelines need to ingest from both the existing SQL Server estate and the new PostgreSQL databases. Core Technical Requirements • Python — primary language for data pipelines, scripting, and integration with the AI stack. This is a Python‐first team, • SQL (SQL Server + PostgreSQL) — deep experience required across both engines. The platform runs a large‐scale multi‐tenant database estate with per‐client schemas (local, global, corporate). The new platform targets Aurora PostgreSQL, with several modules already migrated. Pipelines must bridge both., • Databricks / Apache Spark — a lakehouse POC is being evaluated with Unity Catalog and Delta Sharing via AWS PrivateLink. Experience with Databricks or equivalent analytics platforms is important for assessing and scaling the right approach, • Apache Kafka — event streaming experience is essential. The platform is evaluating Kafka as the strategic backbone for ordered event logs, consumer group replay, and guaranteed partition ordering as the microservices fleet scales, • ETL/ELT pipeline design — building and maintaining pipelines into a medallion architecture (bronze/silver/gold layers) on Databricks or equivalent analytics platform, • Delta Lake — understanding of lakehouse table formats, time travel, and ACID transaction patterns, • AWS data services — RDS, S3, Lambda, Glue or equivalent. The platform runs entirely on AWS • Linux / CLI proficiency — must be comfortable working AI-Assisted Development Methodology -> Solvace is transitioning towards AI‐assisted development as a core engineering practice. Candidates should demonstrate: • Hands‐on experience with AI coding tools — Claude Code, OpenAI Codex, GitHub Copilot, Cursor, or similar. We’re looking for engineers who have integrated these tools into their professional workflow, not just experimented casually, • Spec‐driven development — ability to write clear technical specifications that can be used to drive both human and AI‐assisted implementation, with strong evaluation criteria and test coverage, • Portfolio evidence — professional projects or side projects that demonstrate AI‐assisted development practices. Contributions to or experimentation with emerging projects like OpenClaw are a strong signal, • Testing and evaluation rigour — experience building robust test suites, automated quality gates, and evaluation frameworks that ensure AI‐assisted code meets production standards Nice-to-Have -> • Apache Flink — for real‐time stream processing as the platform moves from batch to streaming analytics, • Apache Iceberg — experience with open table formats alongside or as an alternative to Delta Lake, • Go or Rust — valued as evidence of strong backend engineering and systems thinking, even though Python is the primary language, • Multi‐tenant data architectures — the platform runs per‐client schemas with tenant isolation requirements. Understanding tenant isolation patterns is a significant advantage, • Terraform / IaC — infrastructure is managed via Terraform; the Databricks POC has been codified in Terraform, • dbt or similar transformation framework, • Manufacturing / industrial data domain experience (sensor data, quality metrics, OEE, SPC), • CDC (Change Data Capture) — the platform is building CDC pipelines for the SQL Server to PostgreSQL transition, • Weaviate or other vector database experience — currently used for semantic search in the AI agent layer Why Join? • Greenfield data platform — the entire data engineering practice needs to be built from scratch. A lakehouse POC is being evaluated but the production architecture is theirs to define — patterns, tooling, and platform decisions from day one, • Direct AI impact — every pipeline they build directly unblocks AI agent capabilities. The KAI copilot is live in production and evolving towards agentic AI — autonomous agents that take actions, orchestrate workflows, and operate across systems. This role provides the data foundation that makes agentic capabilities possible, • Event streaming architecture — opportunity to design and implement a Kafka‐based event backbone, shaping the platform’s real‐time data architecture, • Manufacturing AI — opportunity to work at the intersection of industrial operations and generative AI, a domain with massive untapped potential. Rich, real‐world data: quality inspections, KPIs, maintenance records, safety observations, process parameters across global manufacturing sites, • Small team, high autonomy — the Innovation Hub operates with startup‐level autonomy inside a funded, growing company, • Leadership trajectory — the data function is critical to the platform and will grow. As an early hire, there is an open career path that will grow with the function — earned, not guaranteed

Distributed Systems Engineer / Ray Framework SME A fast-growing, early-stage infrastructure company building at the intersection of AI and distributed compute! They’re looking for an Nngineer with strong experience in Python-based distributed computing, strong experience with Ray Framework in particular, to help design and scale systems handling complex, high-throughput workloads. What you’ll be doing • Designing and building distributed systems for large-scale compute workloads, • Scaling Python-based services across clusters and cloud environments, • Working on ML infrastructure / platform tooling (training, orchestration, or inference pipelines), • Improving performance, reliability, and fault tolerance across distributed environments, • Collaborating closely with data scientists and ML engineers to productionise models What they’re looking for • 6-8 years of experience minimum in Systems/Software Engineering., • Strong experience with Ray (e.g. Ray Core, Ray Serve or Ray Tune), • Strong experience with distributed systems or parallel computing, • Solid Python skills (production-level), • Experience with frameworks like Ray, Spark, Dask, or similar, • Exposure to Kubernetes / containerised environments Nice to have • Background in ML infrastructure, data platforms, or backend systems ideal, • Familiarity with PyTorch / TensorFlow in production environments, • Experience building internal platforms or developer tooling, • Cloud experience (AWS, GCP, or Azure) Why join? • Work on genuinely complex distributed problems at scale, • High ownership and impact in a growing team, • Opportunity to shape ML infrastructure from the ground up, • Strong engineering culture with a focus on performance and scalability Location / Package • Ideally London, onsite, but remote will be considered for the right fit., • Up to circa £130k + benefits per annum (dependent on experience)

We're hiring a Gen AI Engineer If you've built LLM systems that actually work in production — not prototypes, not demos — this is worth reading. What our client does They're an AI company operating at the intersection of computer vision and large language models, building intelligent workflows for industries where work happens in the field: utilities, telecoms, energy, retail. Their platform processes real-world operational data at scale, helping global enterprise clients make faster, safer and more accurate decisions about their assets and people. They own a dataset in this space that nobody else has. That matters when you're building AI that actually needs to work. 50+ models in production. Real clients. Real scale. The role You'll own LLM applications end to end. Architecture, prompt engineering, RAG pipelines, eval tooling, guardrails, all of it. No handoffs, no red tape. You build it, you own it. Stack: LangChain / LangGraph, AWS Bedrock, Pinecone / FAISS / Weaviate, DeepEval / Langfuse, Docker, Python. Multimodal capability essential. What we're looking for • 2+ years building and deploying production LLM systems, • Hands-on with RAG, vector databases and retrieval optimisation, • Eval tooling experience: DeepEval, Langfuse, Ragas or equivalent, • Strong Python and LLM orchestration frameworks, • Multimodal LLM experience (text + image/video), • Can own a model autonomously without hand-holding Why join Small senior team. Bi-weekly shipping cycles. Remote-first with optional London office and monthly meetups. Equity, healthcare allowance, pension. The problems are hard. The data is unique. The ownership is real.

Position Summary Be part of the mission to keep the UK safe. We work with Defence & Security clients on some of the most ambitious technology programmes in the country. Our teams are growing across Technology and Transformation — and if you hold UK DV-level Security Clearance, we’d love to hear from you. The Opportunity We’re looking for an experienced Senior Technology Consultant to help digitise defence — combining modern innovation with traditional military functions. You’ll work with clients to solve complex technology challenges, shape cloud strategies, and deliver scalable, secure environments for mission-critical system Key Requirements All applicants must hold active UK DV (Developed Vetting) Security Clearance. Core consulting capabilities: • Strong ability to provide pragmatic, clearly articulated solutions to complex business challenges, • Proven experience managing workloads, meeting deadlines, and delivering tangible results, • Confident communication skills with both technical and non-technical audiences, • Experience leading teams and managing deliverables, • Ability to assess and select vendors/products, • Strong understanding of cloud migration and architecture We’re looking for candidates with skills in one or more of the following areas: Cloud Architecture & Engineering • Cloud platforms: AWS, Azure, Google Cloud Platform, or OCI, • Container technologies (Docker, Rocket) and orchestration (Kubernetes, OpenShift, Rancher, Swarm), • Infrastructure as Code (Terraform, CloudFormation, ARM, GCP CDM), • CI/CD and cloud automation tooling, • DevOps philosophies and toolchains, • Linux and Windows automation frameworks (Ansible, Puppet, PowerShell, etc.), • Version control and deployment tools (Jenkins, SVN, GitHub), • Awareness of cloud security, performance, and non-functional requirements Cloud Consulting • Defining and delivering Cloud Strategy and Operating Models, • Developing business cases for cloud investment, • Product and service selection for cloud solutions, • Leading agile ceremonies and stand-ups, • Architecting and delivering cloud platforms, • Understanding and advising on emerging cloud technologies and challenges, • Maintaining strong relationships with cloud vendors (AWS, Azure, GCP) Technical Authoring • Translating architectural information into clear, technical documentation for engineering and development teams, • Publishing and maintaining network documentation using tools like Git or markup-based repositories, • Managing technical decision processes and facilitating backlog discussions About the Business – Technology and Transformation Distinctive thinking, deep expertise, and a collaborative mindset — that’s what defines us. Our Defence and Security teams support clients to make the UK a safer place. From organisational change and programme management to advanced technology integration, we help clients deliver their mission through innovation and precision. Location and Working Model You’ll be based in Bristol, London, or Manchester, with hybrid working. We understand the importance of balance - so you’ll have the flexibility to work in the office, remotely, or on client sites as needed. Collaboration and connection remain key, but we support adaptable work styles that help you perform at your best.

Staff Software Engineer – AI/ML (Agentic AI) Engineering | UK Remote / London (hybrid) Overview My client is a fast-growing, product-led technology company investing heavily in AI and next-generation machine learning solutions. They are seeking a Staff Software Engineer with experience in agent-based AI systems to help design and deliver advanced AI-driven products. The Role This is a hands-on technical leadership role focused on building scalable AI/ML systems, with a particular emphasis on agentic AI and modern machine learning approaches. You will play a key role in shaping technical direction, establishing best practices, and delivering high-quality systems from concept through to production. The role also involves mentoring engineers and contributing to the growth of a high-performing team. Key Responsibilities Project Ownership • Lead the design and delivery of AI/ML initiatives across the full lifecycle, • Build and deploy models, data pipelines, and production systems Cross-Functional Collaboration • Work closely with Engineering, Product, and DevOps teams, • Support integration of AI capabilities into wider platforms Technical Leadership • Provide guidance on AI/ML frameworks, tools, and best practices, • Contribute to the development of agent-based AI systems and workflows Mentorship & Communication • Mentor engineers and support technical development, • Promote strong collaboration across teams Problem Solving & Optimisation • Identify and resolve challenges in AI/ML systems, • Improve performance, scalability, and reliability Governance & Quality • Ensure high standards around model performance, data quality, and compliance Documentation & Knowledge Sharing • Maintain clear documentation and contribute to internal best practices Skills & Experience • 7+ years’ experience in AI/ML engineering, including production systems, • 3+ years in a technical leadership role, • Strong programming skills (e.g. Python or similar), • Experience with machine learning, data pipelines, and scalable systems, • Knowledge of modern AI approaches, including large language models and agent-based systems, • Experience working with cloud platforms (AWS, GCP, or Azure), • Understanding of distributed systems and scalable architectures, • Experience with CI/CD, microservices, and MLOps practices, • Ability to mentor and support engineers, • Strong collaboration and communication skills, • Experience working in Agile environments, • Degree in a relevant technical field (or equivalent experience) Tech Environment (indicative) • Backend languages (e.g. Python or similar), • Cloud platforms (AWS / GCP / Azure), • Containerisation and orchestration tools, • Infrastructure as code, • Observability and ML tooling, • Modern AI/LLM frameworks, • Relational and non-relational databases, • Version control and CI/CD tooling Benefits • Competitive salary, • 25 days’ annual leave + bank holidays, • Sick pay package, • Flexible / remote working, • Enhanced parental leave, • Pension scheme, • Career development opportunities Additional Information This role is not eligible for visa sponsorship.

Lead AI Engineer Location: Flexible, Europe preferred Type: Full time Overview I am supporting a new AI venture backed by an established global technology platform in digital publishing and print infrastructure. The team is building an AI powered design editor that allows users to generate fully customised, print ready assets from natural language prompts. Unlike template based tools, this system creates original layouts, graphics, and structured outputs end to end. The Role You will operate at the intersection of backend engineering and applied AI, designing and building scalable systems that support production grade AI workflows. This is a hands on role with architectural ownership, focused on taking AI systems from concept through to reliable, high traffic deployment. Key Responsibilities • Design and build backend systems for AI driven content generation, • Develop and scale LLM pipelines, including orchestration and evaluation, • Build agent based workflows for structured content generation, • Architect APIs using Python, FastAPI, and Pydantic, • Ensure systems are robust, scalable, and optimised for production inference, • Collaborate with product and design teams to translate user prompts into structured outputs, • Own performance, reliability, and cost optimisation across AI services Requirements • Strong backend engineering experience with Python, • Proven experience building and deploying LLM based systems in production, • Experience with FastAPI, Pydantic, or similar frameworks, • Hands on experience with RAG, prompt engineering, or agent based systems, • Understanding of system design for high traffic, low latency environments, • Experience working across cloud platforms such as AWS or GCP, • Ability to operate as a senior individual contributor with ownership of architecture and delivery Nice to Have • Experience with generative design, graphics, or structured document generation, • Exposure to multimodal models or layout aware systems, • Background in building tools for creative or publishing workflows

The Setup: A high-growth agile unit within the global STARLIMS ecosystem. STARLIMS provides leading Laboratory Information Management System (LIMS) solutions that have served customers around the world for over 30 years. Our solution suite helps labs: • Improve the reliability of sampling and testing, • Manage complex testing workflows and analytical methods, • Support compliance with global regulatory requirements and industry standards The Role: Architect, Mentor, & AI Pioneer We are looking for a Senior Architect/Lead Developer to take complete ownership of the Labstep platform. You will be the primary decision-maker for our architecture, moving us from a robust data tool to an AI-augmented powerhouse. The Opportunity: The Best of Both Worlds Labstep was founded to build user-centric software that accelerates scientific discovery. Recently, we joined forces with STARLIMS, a global leader in Informatics. What this means for you: You get the high-impact, fast-moving "Day 1" culture of a startup where you own the entire tech stack, backed by the job security, comprehensive healthcare, and professional benefits of a major global organization. • Complete Technical Autonomy: You own the AWS-based stack (Pulumi, ECS, Fargate). You decide the "how" and the "when" for every major architectural shift., • Lead the AI Roadmap: You will architect our AI Search and Natural Language Agent. We want a pragmatic engineer who can lead the implementation of LLMs and Vector Databases to help scientists automate complex tasks., • Mentorship & Team Lead: You will work closely with a Technical Product Manager and mentor a Junior Developer, setting the standard for engineering excellence and clean code., • DevOps Excellence: Managing our infrastructure via Pulumi to ensure the high-availability and security standards required by global research institutions. The Tech Stack: We believe in using the right tool for the job. You will manage the current foundation while evolving it: • Current Core: PHP 8 / Symfony / Doctrine API, React / TypeScript Frontend., • Cloud/Infra: AWS (Fargate, ECS, Lambda), Pulumi (IaC), MySQL., • The Frontier: This is your domain. You will lead our transition into Vector Search, Hybrid Search Engines, and AI Orchestration. Who You Are: • A Technical Owner: You’ve scaled production web apps and are comfortable across the full stack and infrastructure., • Pragmatic AI Enthusiast: You don't need a background in AI, but you are excited to build production-ready AI features (RAG, Agents) that solve real problems., • Empathetic Mentor: You enjoy leveling up junior talent and collaborating deeply with product peers., • Mission-Driven: You want your work to help scientists cure diseases and solve global challenges. Skills Required: • 5+ years of leading development teams, • 5+ years of leading architect, • 5+ Years of AWS DevOps experience, • Experience coding with the following languages/technical solutions - PHP 8 / Symfony / Doctrine API, React / TypeScript Frontend Why Labstep & STARLIMS? • Impact: Your code directly supports the world’s leading scientists and researchers., • Stability & Perks: Enjoy the comprehensive benefits package of a large corporation—including private healthcare, pension, and enhanced job security—without the corporate red tape., • The "Startup" Feel: We remain a small, agile team that moves fast, experiments often, and values your voice., • Work-Life Balance: Remote-first flexibility with meaningful monthly in-person collaboration in London. STARLIMS is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, creed, religion, color, national or ethnic origin, citizenship, sex, sexual orientation, gender identity and expression, genetic information, veteran status, age or disability status.

Job Title: GCP Data Engineer (DBT, Cloud Composer, Python, Terraform) Location: Edinburgh / Leeds/Halifax (hybrid 2/3 days from office) Experience: 10+ years Role Overview We are seeking an experienced GCP Data Engineer with strong expertise in DBT, Cloud Composer, Python, and Terraform Required Skills & Experience • Strong hands-on experience with Google Cloud Platform (BigQuery, Cloud Storage, etc.)., • Proven experience in DBT for data transformation., • Expertise in Cloud Composer / Apache Airflow for workflow orchestration., • Advanced proficiency in Python., • Solid experience with Terraform for infrastructure provisioning., • Demonstrated experience in migrating legacy systems (on-prem or other cloud) to GCP., • Strong understanding of data warehousing concepts and ETL/ELT frameworks., • Experience in leading teams and managing end-to-end delivery.

Senior ML & AI Engineer Remote Up to £80,000 About the Role We’re partnered with a fast-growing tech startup focused on how brands and retailers use data. Their AI platform brings together data science, immersive visualisation, and large-scale machine learning to optimise product ranges, plan shopper journeys, and drive smarter commercial decisions. They’re now looking for a Senior ML & AI Engineer to join their lean, high-impact engineering team. This is a pivotal role at the intersection of ML engineering, backend systems, and LLM integration - ideal for someone who thrives in fast-paced, hands-on environments where ML systems are core. Responsibilities • Design, build, and maintain scalable backend systems that power advanced ML and LLM applications., • Develop and manage end-to-end MLOps pipelines with automation, reproducibility, and scalability at their core., • Deploy and monitor machine learning and LLM models in production, identifying model drift and performance issues., • Drive research and development in modern ML, AI, and LLM approaches, applying SOTA techniques in a real-world setting., • Champion clean, maintainable, and well-documented code following best engineering practices. What We’re Looking For • Strong academic background in Computer Science, ML, AI, or a related field., • Deep hands-on experience with Python and ML frameworks (PyTorch, TensorFlow, Hugging Face)., • Proven background in MLOps, including model versioning, CI/CD for ML, and production monitoring., • Experience building robust backend systems and APIs to serve ML models at scale., • Strong understanding of big data technologies and data orchestration tools (Airflow, DBT)., • Familiarity with LLM integration and optimisation in production environments., • Excellent problem-solving, analytical, and communication skills., • Experience fine-tuning LLMs (e.g. Unsloth, cloud-based methods).

Do you want to build AI systems that power real financial intelligence used by hedge funds? Have you deployed LLM or RAG systems into production rather than just prototypes? Are you ready to design agentic AI systems end-to-end in a small, high-ownership engineering team? A London-based alternative data company is hiring an AI Engineer to help build production AI systems used internally and eventually within client-facing products. The company develops machine learning models that estimate company performance before earnings announcements by analysing alternative datasets such as transaction data, digital signals, and web activity. Their platform tracks hundreds of public companies and sells predictive KPI insights to hedge funds and institutional investors. The team is small and highly technical, offering engineers significant ownership across architecture, tooling, and product development. This role will focus on designing and deploying end-to-end LLM systems, initially building internal AI tools and automation systems before expanding into client-facing AI products. Key Responsibilities • Design and deploy RAG pipelines for knowledge retrieval and reasoning, • Build agentic AI workflows using frameworks such as LangChain or similar, • Develop LLM microservices using Python frameworks such as FastAPI or Flask, • Build internal AI tools including chatbots, automation systems, and workflow assistants, • Deploy AI services on AWS infrastructure and manage reliability and monitoring, • Work with vector databases and orchestration frameworks for LLM systems Key Details • Comp: £60,000–£95,000, ~15% bonus, equity, • Working model: Fully remote (UK) with occasional team gatherings, • Tech stack: Python, LangChain, RAG systems, AWS, vector databases, • Visa sponsorship: This role cannot sponsor Interested? Please apply below.

Location: Remote (UK/EU preferred) Type: Freelance Contract (Part-time ad-hoc, project-based, potential for long-term collaboration) Hours: Work on your own schedule but must be available for 1 meeting per week during UK working hours. About WineFi WineFi is a data-driven platform for fine wine investing. We combine financial modelling, machine learning, and deep domain expertise to uncover undervalued wines and select assets that outperform the wider wine market. Our work bridges quantitative finance and alternative assets, helping investors make smarter decisions in an opaque market. The Role We’re seeking a freelance Backend / API Engineer to design and build production-grade APIs that expose our proprietary wine market data to our platform and external stakeholders. This role is ideal for someone with experience building clean, reliable, and well-structured APIs on top of complex data systems. Your first project will be to design and build a robust external-facing API layer that serves curated datasets from our internal databases. Over time, you may play a key role in improving how our data systems integrate with our platforms. Requirements • Proven experience as a Backend Engineer / API Engineer (3+ years), ideally in a startup or freelance environment., • Strong Python programming skills (FastAPI, Flask, or similar frameworks), • Experience building and maintaining production APIs used by external clients, • Strong SQL skills, including query optimisation and schema understanding, • Experience working with PostgreSQL;, • Familiarity with AWS (e.g. EC2, RDS, Lambda, API Gateway, etc.), • Experience with API security (authentication, rate limiting, key management), • Strong communicator, able to work independently and asynchronously Nice-to-have • Familiarity with ETL pipelines and orchestration tools (Dagster, Airflow, Prefect), • Experience with Motherduck, DuckDB, Dagster, dbt and Modal also beneficial., • Exposure to financial, time-series, or alternative asset datasets Responsibilities • Design and build scalable, production-grade REST APIs in Python., • Structure endpoints for both internal platform use and external clients/partners, • Implement authentication, rate limiting, and access control for external users, • Build efficient data access layers on top of PostgreSQL and internal data models, • Optimise query performance and API response times, • Ensure high availability, logging, and monitoring of API services, • Help define best practices for API structure, versioning, and maintainability, • Contribute to the broader architecture connecting data pipelines, databases, and application layers Collaboration • Work closely with data scientists and the head of data to align API outputs with models and research., • Support frontend/platform needs for seamless data consumption. Why work with us? • Freelance flexibility with potential for long-term collaboration -- we have lots to build!, • A lean, ambitious environment where your work has direct impact, • The opportunity to build the core API layer of a data-driven investment platform, • Work closely with the founding team across data science and engineering Unedited, AI-generated applications and messages are highly discouraged. Please start any message to us with 'original' and keep them under 100 words.

Location • Remote, but requirement to meet up once a month for in-person collaboration day, • UK based About Akixi Akixi is a fast-growing SaaS analytics company delivering real-time and historical insights for cloud-based communication platforms, including Microsoft Teams, Cisco BroadWorks, and Webex Calling. Our analytics help businesses enhance customer experience, optimize productivity, and drive performance across voice and collaboration channels. Job Summary We are seeking a Senior Platform Engineer with a deep understanding of AWS cloud infrastructure, Infrastructure-as-Code (IaC) tooling such as Terraform, and configuration management using Ansible. The ideal candidate will be a self-starter, passionate about Site Reliability Engineering (SRE) principles, and thrive in collaborative environments. You will play a pivotal role in automating infrastructure, improving reliability and scalability, and ensuring smooth CI/CD pipelines across multiple environments. You'll work closely with software engineering, and security teams to drive platform excellence. Key Responsibilities • Design, build, and manage scalable, secure, and resilient infrastructure on AWS using Terraform (modularized, reusable components)., • Implement configuration management solutions using Ansible, including playbook development, inventory structuring, and role-based automation., • Manage secrets securely using services such as AWS Secrets Manager or HashiCorp Vault., • Implement robust monitoring, alerting, and observability tooling (e.g., CloudWatch, Prometheus, Grafana, Datadog)., • Participate in incident response, root cause analysis, and resilience improvements., • Maintain and evolve CI/CD pipelines using tools such as GitHub Actions, Bitbucket Pipelines, or Jenkins., • Automate deployments for container-based workloads on ECS (Fargate), or Lambda, and manage supporting infrastructure., • Collaborate with development teams to optimize build/deploy cycles and reduce lead time for changes., • Ensure security best practices are embedded into infrastructure provisioning and pipeline execution., • Support compliance and auditing by implementing guardrails and controls as code (e.g., AWS Config, SCPs, IAM policy management)., • Some OOH work is required to maintain the production systems and also will be part of OOH critical ticket rota. Required Skills & Experience • 5+ years in DevOps, SRE, or Cloud Engineering roles., • Expertise in AWS core services: EC2, IAM, VPC, ECS/Fargate, CloudFormation, CloudWatch, RDS, DynamoDB, S3, Lambda., • Strong proficiency in Terraform (HCL) – including workspaces, modules, and Terraform Cloud or similar., • Ansible experience – developing roles, dynamic inventories, managing remote configurations., • Strong scripting knowledge (Bash, Python, or Go)., • Experience with container orchestration and deployment (Docker, ECS, or Kubernetes)., • Proficient with GitOps or IaC-based workflows., • Familiarity with Google SRE practices, particularly around reliability, observability, and operational excellence., • Understanding of systems reliability metrics and associated tooling Soft Skills & Behaviours • Self-driven with a bias toward action and ownership., • Excellent communicator, able to collaborate across disciplines and levels of technical understanding., • Experience working as part of a cross-functional team., • Comfortable working in agile environments (Scrum/Kanban).

Job Title - Senior Golang Engineer Rate - Competitive (Outside IR35) Location - Remote from UK & Europe Role Overview The Senior Backend Engineer will play a key role in building and scaling robust backend systems for a high-growth, multi-region platform. This position focuses on developing resilient, high-throughput services within a distributed, event-driven environment, supporting critical domains such as payments, accounts, and transaction processing. Core Responsibilities • Design, develop, and optimise backend services using Golang., • Build scalable, fault-tolerant microservices within a distributed architecture., • Develop and maintain RESTful APIs and internal service-to-service communication layers., • Work across core platform areas including payments, accounts, ledger, and risk/compliance systems., • Ensure code quality through peer reviews, testing, and adherence to engineering best practices., • Monitor and support live systems, troubleshooting and resolving production issues., • Collaborate closely with cross-functional teams including Product, DevOps, and Compliance. Required Experience • Strong hands-on experience developing backend services in Golang., • Solid understanding of concurrency, system performance, and efficient resource management., • Proven experience designing and building microservices and distributed systems., • Experience working with containerisation and orchestration tools such as Kubernetes., • Familiarity with cloud platforms (AWS, GCP, or Azure)., • Previous experience in fintech, regulated environments, or high-transaction systems is highly desirable. If this is of interest then please apply, we would love to hear from you!

Company Description AI agents are becoming autonomous - they execute code, call APIs, and make decisions without human oversight. An adequate security approach to govern them doesn't exist yet. We're building it. Our founding team created Sigstore, the open-source signing standard now used by npm, PyPI, Kubernetes, and other critical infrastructure. We're applying that same thinking to agentic security: execution boundaries, immutable attestation, and dynamic capability management for AI agents. This is a UK based role, but we may consider hiring from Europe and the US East Coast for exception candidates. What You'll Do • Contribute directly to the Nono open source project - code, documentation, and architectural proposals., • Experiment with different deployment architectures for Nono across cloud environments, on-premise infrastructure, and hybrid setups and share your findings with others at Always Further, and often with the community, via our blogging platforms or YouTube channel., • Work closely with early design partners to integrate Nono into proof-of-concept and pilot programmes, gathering feedback and translating it into engineering priorities., • Support pre-sales and post-sales engineering conversations with tier-1 enterprise organisations., • Produce technical content - blog posts, architecture guides, demos - that helps users and customers get the most out of Nono. What We're Looking For • AI engineering experience. You understand how modern AI/ML workloads are built, deployed, and orchestrated. Familiarity with agent frameworks and LLM-based systems is a strong plus., • Rust and Python proficiency. You don't need to be a language lawyer in either, but you should be comfortable reading, writing, and reviewing code in both. Rust experience is especially important for contributing to Nono's core, while Python is often used for tooling, research integration, and customer-facing scripts., • DevOps and cloud fluency. You've worked with container orchestration, CI/CD pipelines, and at least one major cloud provider (AWS, GCP, Azure) and some familiar with others.. Infrastructure-as-code is a strong point., • Security background. Understanding of host isolation, sandboxing, and supply chain security is highly valued. If you've worked on container security, VM isolation, or trusted execution environments, even better., • Open source experience. You've contributed to or maintained popular open source projects and understand how healthy communities operate - governance, code review culture, release processes, and community engagement., • Strong communication skills. You're equally comfortable in a GitHub issue thread with community contributors and in a room (or on a call) with enterprise architects and CISOs. Nice to Have • Background in systems programming, low-level Linux, or virtualisation technologies., • Strong hands on architectural knowdledge of how to deploy and operate complex distributed systems in production., • Familiarity with AI agent security challenges - prompt injection, tool misuse, data exfiltration, lateral movement., • Previous experience in a solutions engineering, or field engineering role at a startup or open source company. Why Join Always Further • Foundational impact. You're not joining a team — you're building one. Your architectural decisions become the product., • Foundational Stake & Compensation. As an early foundational hire at a pre-seed company, you will receive a highly competitive equity stake designed to reward early risk-taking and outsized impact, paired with a pre-seed base salary., • Remote, UK preferred. We're UK-based but open to exceptional candidates wherever they are. We provide flexible working built on trust and ownership., • Interested? Send us your CV along with your GitHub profile that links to any relevant open source contributions, blog posts, or projects. A short note on why this role interests you goes a long way.

Head of AI is seeking exceptional leaders to join our network of fractional Heads of AI. Our mission is to help Biotechnology and life sciences organisations evolve into AI-enabled institutions — embedding AI strategically across their research, development, operations, and decision-making. We are looking for individuals who combine deep technical fluency with board-level leadership, capable of guiding organisations as they adopt and scale the new era of generative and agentic AI. We work with organisations across biopharmaceuticals, drug discovery, genomics, clinical research, digital health, and medical devices, typically ranging from £20m–£500m+ in revenue. These organisations face increasing pressure to accelerate innovation and improve patient outcomes while maintaining strong governance, regulatory compliance, and data integrity. Our fractional Heads of AI support leadership teams in embedding AI capabilities that improve R&D efficiency, strengthen decision-making, and unlock new scientific and commercial value. We recognise that few professionals have completed a full AI transformation in life sciences. Therefore, we seek leaders with proven experience in digital, data, analytics, or operational transformation who are now applying that expertise to AI-led change. You understand how to translate ambition into action — guiding organisations through the cultural, operational, scientific, governance, and regulatory shifts required to unlock AI’s potential. What We Are Looking For: AI-Driven Business Transformation Leaders: Proven experience leading complex transformation programmes where technology, data, and innovation reshaped business performance. Able to apply that experience to the generative AI era — guiding biotech and life sciences organisations through the shifts required to become AI-enabled. Can connect earlier digital, analytics, or automation expertise with today’s agentic and generative AI capabilities. Deep Technical Fluency: Fluent in modern AI ecosystems including generative AI, agentic systems, AI copilots, and orchestration frameworks (e.g. LangChain, AutoGen, CrewAI). Understands how to combine traditional ML, analytics, and scientific data systems (e.g. genomics, clinical, real-world data) with emerging AI architectures to deliver measurable value. C-Suite and Board-Level Communicators: Able to simplify complex AI and scientific topics for executives and align AI investments with organisational strategy. Confident advising CEOs, CTOs, Chief Scientific Officers, and Boards on strategy, risk, governance, and ROI. Change Leaders: Strong stakeholder engagement and ability to drive adoption. Skilled in mentoring teams, developing AI literacy, and ensuring responsible AI practices. Understands data governance, regulatory requirements (e.g. GxP, FDA/EMA), and human-in-the-loop design needed for AI success in life sciences. Entrepreneurial Mindset: Thrives in ambiguity and fast-paced environments. Curious about new AI tooling and pragmatic about implementation. Focused on delivering measurable outcomes through experimentation and iteration. What We Are Not Looking For: • Legacy executives without hands-on AI or GenAI understanding, • Academic or research-focused professionals without applied business outcomes, • Technologists who lack leadership or transformation delivery experience, • Consultants who only advise but have not led execution, • Corporate-only leaders reliant on large structures Desired Profile Summary The ideal candidate will serve as a Fractional Head of AI / AI-Driven Transformation Leader, focused on helping biotech and life sciences organisations design and execute end-to-end AI strategies, roadmaps, execution plans, and governance frameworks. They will bring 10–20+ years of experience across AI, data, digital transformation, analytics, or life sciences innovation, with a proven ability to translate technology into measurable scientific and commercial outcomes. They are experienced transformation leaders — such as Heads of Data Science, Chief AI Officers, AI Strategy Leads, or Digital Transformation Leaders — who have evolved beyond model development into organisational change and value delivery. Candidates with a data science or bioinformatics foundation are welcome, provided they demonstrate fluency in modern AI technologies (LLMs, copilots, orchestration frameworks) and executive-level influence. They thrive in fractional roles (1–5 days per week) and bring an entrepreneurial, adaptable, and outcome-driven mindset. We welcome applications from professionals passionate about helping life sciences organisations harness AI responsibly and at scale.

Role: Senior AI Engineer Location: Remote (UK-based) Type: Full-time, permanent Compensation: Competitive salary + equity available About Veridox Veridox detects fraud in documents and images submitted to insurance companies, airlines, and financial institutions. When someone submits a receipt, ID document, or damage photograph, our platform determines whether it's genuine, tampered with, or AI-generated and explains why. Under the hood, we’re replacing brittle, hand‑wired pipelines with multi‑agent AI that reasons more like a human forensic analyst: pulling signals from multiple tools, weighing messy, conflicting clues, and landing on clear, defensible decisions. The Role You'll work on the core AI systems that make fraud decisions. This means building and improving the agent pipelines that coordinate LLMs, VLMs, OCR and forensic tools. You won’t be just calling APIs, but designing how autonomous agents reason about complex, ambiguous evidence. Day to day, you might be: • Improving how the system handles a document type it's getting wrong, • Designing a new agent reasoning pattern (e.g., cross-referencing findings across multiple documents in a claim), • Debugging why an agent produces inconsistent verdicts on edge cases, • Deploying pipeline changes to AWS and monitoring real-world performance, • Writing tests that verify an agent makes the right routing decision when evidence conflicts The work sits at the intersection of AI engineering, systems design, and a surprisingly interesting fraud detection domain. Builder Mindset We’re looking for people who build systems, not just talk about them. This role is about shipping reliable AI into production: debugging edge cases, improving pipelines, and learning from real-world behaviour. If you enjoy turning ideas into working software and iterating quickly, you’ll fit right in. What We're Looking For You should be strong in: • Python: you write clean, typed code and care about it working correctly at the edges, • Working with LLMs beyond chat: structured output, multi-step reasoning, prompt calibration for reliability, • AWS: comfortable with S3, Lambda, IAM, and deploying services that need to work without you watching them, • LLM/VLM Observability (e.g Arize Phoenix), • Experience with agent orchestration frameworks (LangGraph, LangChain, or similar), • Familiarity with vision-language models for image analysis, • Some exposure to document analysis, OCR, or fraud detection, • The specific AWS services we use (Bedrock AgentCore, EventBridge), • Our domain (insurance fraud, document forensics), • The exact frameworks in our stack These are learnable. What matters more is that you can reason about systems, write reliable code, and think critically about how AI makes decisions. How We Work • Small team, high autonomy, async-first, • Security-conscious by default. We assume all inputs are hostile, • We'd rather halt and ask a question than ship something we're uncertain about, • Code gets attacked before it ships. We review from the perspective of a hostile auditor, • We don't over-engineer. Three similar lines of code is better than a premature abstraction What Growth Looks Like Early on: You're deploying changes to the pipeline, understanding how evidence flows through agents, and shipping features that touch the reasoning layer. Later: You own major subsystems. The document analysis agent, the tool orchestration layer, or the cross-document case analysis pipeline. You're making architectural decisions about how agents reason. Longer term: You're designing novel multi-agent patterns, integrating new forensic tools, and shaping how the platform learns from analyst feedback over time.

Profile 29 recruitment keywords: Site Reliability Engineer Site Reliability Engineering, DevOps Kubernetes container orchestration Red Hat OpenShift Terraform Amazon Web Services AWS CI/CD Bash Python monitoring observability cloud architecture London hybrid remote AI artificial intelligence securit

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