About the Role

We're looking for an Engineering Manager to lead our Infrastructure team as we grow. You'll own the infrastructure, deployment pipelines, and reliability behind Pivotal's platform: infrastructure as code, CI/CD (the automated pipelines that test and ship code), uptime, monitoring, alerting, and observability.

The work runs on two tracks. You'll keep today's systems healthy on GCP with Terraform, GitHub, and serverless Cloud Run, and you'll lead the building of an agentic-first CI/CD workflow, where AI agents carry routine delivery work like speculative deployments and new dev environments. The team's on-call rotation is already in place and mostly runs during working hours.

This is a high-accountability, player-coach role. Our engineers across the company depend on the platform you run, and the problems are often ambiguous. You'll lead an experienced team working closely with engineering partners across Product Engineering, Data Science, and AI Platform, and stay close enough to the technical work to guide architecture and debug production issues alongside the team. The right person will find that combination energizing.

This is a small team with real ownership and no bureaucracy, so decisions reach production quickly. You'll thrive here if you use AI every day, debug production issues to root cause, and explain your reasoning clearly.

What You'll Do

Lead the team

• Lead an experienced engineering team: Set clear priorities, coach engineers, create accountability, and make sound decisions while preserving the rigorous technical debate that makes the team stronger.

• Grow and structure the team: Hire additional engineers and establish the roles, ownership boundaries, and operating practices the team needs as its scope expands.

• Drive predictable delivery: Turn ambiguous infrastructure and platform problems into clear plans, sequence the work, manage dependencies, and make sure the team ships meaningful improvements consistently.

• Balance building and maintaining: Keep the systems we run today stable while the team builds what comes next, and make the tradeoffs between the two explicit.

Own the platform

• Own infrastructure as code: Ensure Pivotal's Terraform on GCP keeps every environment reproducible, reviewed, and version controlled.

• Own CI/CD: Run the pipelines that take code from GitHub to production on Cloud Run, and keep them fast, reliable, and easy for engineers to use.

• Build the agentic-first CI/CD workflow: Lead the design of delivery workflows where AI agents handle routine work, including speculative deployments and spinning up new dev environments.

• Drive uptime and reliability: Keep production healthy, drive production issues to root cause, and make sure the underlying cause is fixed so the same problem does not return.

• Define monitoring, alerting, and observability: Build the signals that tell us something is wrong before our customers do, and tune alerts so they are worth waking up for.

• Run a healthy on-call rotation: Support the team's on-call rotation, participate as needed, and improve it as you learn where it hurts.

• Shape the technical direction: Guide architecture and scaling decisions for deployment systems and GCP infrastructure, bringing a clear point of view and partnering with engineers across the company in architecture reviews.

Use AI to stay close to the work

• Automate toil with AI: Find manual, repetitive infrastructure work and replace it with AI-driven automation, and use AI-enabled development tools in your own daily work to explore ideas, prototype solutions, and contribute directly when doing so accelerates the team or improves a technical decision.

Who You Are

• 8+ years supporting highly available production systems, including debugging production issues under pressure

• 1-3 years as a tech lead and/or engineering manager

• Hands-on infrastructure experience, including Infrastructure as Code with Terraform, and enough technical depth to guide architecture, evaluate tradeoffs, and earn the trust of experienced engineers

• Observability and on-call experience

• Working experience with GCP, GitHub, and serverless platforms like Cloud Run

• Real day-to-day AI fluency

• Experience on a small team where you owned systems end to end rather than one narrow slice of a large organization

• Experience leading through ambiguity, forming clear points of view without waiting for every question to be resolved

• Experience managing an experienced, opinionated team, creating clarity and making decisions without shutting down productive disagreement

• A clear communicator who can explain technical tradeoffs to engineers and non-engineers alike, and create alignment across Engineering, Product, and other partners

Extra credit if you have:

• Experience leading architecture and scaling decisions for deployment systems

• Experience scaling an early engineering team

• A startup or agency background working across many different stacks and problems

• Experience building AI-agent-driven or AI-assisted developer workflows

• Experience in healthcare, provider reimbursement, revenue-cycle management, claims, or Independent Dispute Resolution

Benefits Include:

• Competitive compensation, including equity

• Full health, dental, and vision coverage

• Retirement savings plan through 401(k)

• Flexible time off

• Opportunities for company-wide connection and events

Employment Information