Senior Full Stack Engineer w/ AI Tooling (RQ96)

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 pipelines 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