Staff Software Engineer (AI-Focused)
2 days ago
New York
Job DescriptionSalary: $180,000 to $205,000 About NYSHEX NYSHEX is transforming the shipping industry through a unified digital infrastructure that connects shippers, carriers, and NVOCCs. Our mission is to solve the problem of contract fulfillment by combining reliability, automation, and transparency. As we scale, were embedding generative AI and intelligent automation across our engineering stackfrom developer productivity and testing to observability and security. Role Summary As a Staff Software Engineer at NYSHEX, you will be a senior technical leader who is hands-on with delivery, while influencing system architecture, design decisions, and team mentorship. You will balance deep technical contributions with strategic alignment across engineering, product, and platform initiatives - especially as we evolve into an AI-first engineering organization. This role is ideal for an experienced engineer who thrives in ownership, collaborative delivery, and is excited by the opportunity to pioneer the use of AI tools in software development, security, documentation, and product innovation. Located in One World Trade Center, NYC this is a hybrid role (In-office Monday through Wednesday) and reports to the CTO. Key Responsibilities Technical Leadership & AI-Augmented Execution Architect and implement complex systems with scalability, performance, and security in mind. Champion an AI-first approach across design, development, testing, and code reviews. Leverage GenAI tools like Cursor, GitHub Copilot, Amazon CodeWhisperer or ChatGPT CLI for boilerplate generation, code suggestions, documentation, and testing. Set and enforce engineering standards, including achieving 85% test coverage. System Design, Observability & Reliability Own critical system components and ensure adherence to clean code, modular patterns, and service reliability. Integrate observability tools (e.g., Datadog or New Relic with anomaly detection) to detect issues proactively. Lead incident response using incident summaries and LLM-enabled remediation paths. Delivery & Impact Deliver high-quality, tested, and well-documented software features on time and in full. Plan and estimate work collaboratively with product and engineering teams, using a strong understanding of technical tradeoffs. Identify and resolve tech debt, bottlenecks, and security vulnerabilities before deployment. Ensure instrumentation and alerting are in place to support continuous improvement. Mentorship & Technical Enablement Mentor other engineers through design reviews, pair programming, and AI-assisted collaboration. Guide responsible integration of GenAI into daily workflows (e.g., code gen, unit test generation, secure coding). Contribute to shared architectural decision records (ADRs) and technical documentation. Cross-Functional Collaboration Work closely with Product Managers, Data Science, and Platform teams to embed AI into customer-facing features and internal tools. Evaluate and introduce AI agents (e.g., Slack bots, GitHub automation) to accelerate engineering operations. Tech Stack Languages & Frameworks: Java (Spring), Python JavaScript/TypeScript (Next.js, Node.js) is a plus REST APIs Kafka GraphQL, PostgreSQL, Aurora Cloud & Infrastructure: AWS (EC2, S3, Lambda, SES, SNS, SQS, Step Functions, Kafka, etc.) Kubernetes, Docker AI Developer Productivity and Quality Tools: Cursor, GitHub Copilot, CodeWhisperer, ChatGPT CLI SonarQube (AI rulesets), CodeQL, DeepSource Snyk, AWS Inspector Monitoring & Observability: Datadog, New Relic, OpenTelemetry, CloudWatch CI/CD & Automation: GitHub Actions, AI-generated tests and release steps Terraform / AWS CDK Key Performance Indicators (KPIs) AI-Enabled Software Development Productivity: 50% of PRs use AI-assisted tooling Code Quality: 85% test coverage and secure code practices Delivery: Consistent on-time, in-full delivery of key product features System Reliability: 99.95% uptime for owned services Mentorship Impact: Regular contribution to team enablement and tooling adoption Required Qualifications 8+ years of professional experience building scalable, distributed systems Strong knowledge of backend service architecture, event-driven design, and microservices Hands-on experience with GenAI tools and integrating AI into engineering workflows Excellent communication and mentorship skills Experience with cloud-native development (preferably AWS), CI/CD pipelines, and observability tooling Preferred Qualifications Experience with LLM integration (OpenAI, Bedrock, Anthropic) Exposure to prompt engineering and model lifecycle workflows Familiarity with security best practices (e.g., OWASP Top 10, OAuth, SAML) SaaS product experience with a focus on performance, observability, and automation Contributions to open-source or AI/DevEx tooling communities What We Offer Forward-thinking, AI-first engineering culture Unlimited PTO and flexible hybrid schedule Health, mental wellness, and family planning benefits Annual team offsites and internal AI demo days Opportunities to lead architecture, AI strategy, and engineer enablement