Staff Engineer, DevOps

We operate a multi-tenant automotive SaaS platform serving thousands of dealer groups across the United States. Our backend — event-driven serverless on AWS — orchestrates everything from dealer onboarding to inventory management to real-time transaction processing. That platform works. Now we need to make it think — and keep it modern, secure, and safe to ship. We also run a monolith that needs upkeep while we build the next-gen platform and redesign its components, a few at a time, into microfront ends.

This is a hands-on engineering role at its core. Day to day you build, ship, and operate agentic AI systems — autonomous, tool-using agents (Agent Core, MCP servers) that observe platform state, reason over dealer context, and take action through production APIs. But you are also the engineer who keeps the whole platform current and trustworthy: you continuously hunt and fix security vulnerabilities, upgrade the frameworks and runtimes underneath us, drive adoption of an agentic development harness to speed up delivery, and lead modernization of our existing systems.

You work across the org, not inside one team's walls. You own production monitoring and the SRE practices that keep us reliable, and you are the champion for safe releases — defining the checks and balances that gate production, setting the engineering standards, and making sure they are actually enforced. When something misbehaves in production, your instrumentation, your guardrails, and your release discipline are what make it fail safe instead of fail loud.

Reports to:

SVP, Engineering.

• Hands-on agentic development — designing, building, and operating agentic AI systems (AWS Bedrock Agent Core, MCP servers) every day: agent code, tool interfaces, evaluation harnesses, and production AI workflows.
• Driving adoption of the agentic development harness — making agent-assisted development a first-class way the org ships, and measurably improving speed of delivery across teams.
• Security vulnerability management — continuously monitoring for vulnerabilities (dependencies, CVEs, container images, IAM/config drift), remediating quickly, and keeping frameworks, libraries, and runtimes patched and upgraded.
• Platform modernization — creating and driving initiatives to modernize existing platforms: retiring legacy patterns, adopting current frameworks, and staying close to the leading edge.
• Production monitoring & SRE — owning observability (Open Telemetry, Cloud Watch), SLOs and error budgets, on-call and incident response.
• Third-party integration observability — a standardized way to organize all third‑party integration calls, report on them with precision, and run anomaly detection on call volumes with continuous monitoring, so a spike, drop, or failure surfaces before it becomes an outage or a cost problem.
• On‑call cookbook — keeping applications well documented so an on‑call engineer can quickly query a cookbook, understand the likely problem areas, and know where to look.
• Release governance — champion across releases: defining and enforcing the checks and balances (CI/CD quality gates, security and test gates, rollback criteria, progressive delivery) required to move change into production.
• Setting and enforcing engineering standards — establishing the patterns, guardrails, and review bar the org follows, and holding the line so they are consistently applied.
• Working across the org — partnering with every engineering team to raise the technical, security, and reliability bar broadly.

• Cloud:
  Lambda, Event Bridge, DynamoDB, S3, ECS Fargate, Aurora, API Gateway, Cloud Watch, Secrets Manager.
• AI & Agentic: AWS Bedrock Agent Core, MCP servers, Lang Chain/Lang Graph.
• Languages:
  
  Python and Java (Spring Boot),…