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About the role
Senior Full Stack Engineer w/ AI Tooling
Candidate must be local, willing to interview onsite & work onsite 3-days/week
Overview: Builds platforms, tooling, and automation that augments our SDLC — production services, CI/CD integrations, testing infrastructure, and observability — increasingly augmented by AI agents and LLMs. We're looking for a strong full-stack engineer first, who is also fluent with modern AI tooling.
What We're Looking For
You are a strong full-stack engineer who ships end-to-end — design, tests, CI/CD pipeline, deploy, and production monitoring — and treats every stage as first-class craft rather than overhead. You have clear technical taste, articulate trade-offs well, and know when to reach for an AI agent versus a simpler tool. You use modern AI development tools fluently in your daily workflow and have a grounded point of view on where they help and where they don't. You iterate based on real usage data and telemetry, not intuition alone. Key Responsibilities: Platforms & Tooling Builds and operates CI/CD p ipelines and integrations Build "Golden Path" scaffolding with standards, security, and quality gates built ins Build & Maintain a governed catalog (Agents, MCPs, Skills) with behavior, permission, and access control Build AI agents, LLM-powered tooling, and the frameworks and SDKs that accelerate them Build integrations that give humans and AI agents deep context on our systems Quality, Testing & Reliability Own testing strategy across the platform: unit, integration, contract, and end-to-end Apply mutation, property-based, or fuzz testing where it pays off Define SLOs for platform services and AI toolin Observability & Performance Analytics Design metrics, logs, traces, and dashboards for productivity, adoption, and service health Build alerting and anomaly detection to catch regressions early Analyze telemetry to guide investment decision Collaboration & Impact Partner across teams to drive adoption of platform tooling and AI-augmented workflows Stay current with LLM and platform-engineering trends and coach colleagues on where they apply Rapidly prototype solutions to validate use cases Communicate insights to stakeholders Required Qualifications: 5–7+ years building and operating production software systems Full-stack proficiency across Java, Python, and TypeScript/JavaScript, with frameworks like Spring Boot and Angular Deep CI/CD experience — Jenkins, GitLab, or equivalent; comfortable with IaC Testing discipline — TDD, test pyramid design, integration and contract testing AWS fundamentals — ECS, EC2, Fargate, Lambda, API Gateway Observability — metrics, logs, traces; CloudWatch or Splunk Daily use of AI coding tools — Claude Code, Kiro, Codex, or equivalent, with a clear point of view on their limits Nice to Have: Building internal developer platforms, SDKs, or CLIs at scale LLM orchestration in production — MCP servers, agents, tool calling Advanced testing (mutation, property-based) or driving platform adoption across teams
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