Senior Software Engineer – Developer Productivity

Senior Software Engineer – Developer Productivity (Python)
About the Role

We are building the engineering foundations required to develop, evaluate and deploy AI systems at government scale.

As a Sr Software Engineer, Developer Productivity
, you will build the platforms, tooling and workflows that enable engineers to move quickly while maintaining the security, reliability and governance expected of government systems.

Your mission is to create a world‑class developer experience—removing friction across development, testing, AI evaluation, CI/CD and deployment
.

You’ll be a hands‑on engineer, writing production code and working closely with AI, platform and application teams to shorten the loop from idea → build → evaluate → deploy
.

• Build developer platforms and tooling used across AI engineering teams.
• Create fast, reproducible development environments across macOS, Windows and Linux.
• Build and improve CI/CD, build caching, merge queues, automated testing and deployment pipelines.
• Develop infrastructure supporting LLM, agent and AI evaluation workflows
  .
• Improve parity between local, CI and production environments.
• Automate developer provisioning, onboarding and environment configuration.
• Build observability around builds, tests, evaluations and deployments.
• Identify engineering bottlenecks and automate them away.
• Enable engineers to experiment quickly while meeting government requirements around security, data sovereignty and reliability
  .

• Have strong software engineering fundamentals and regularly write and review production code (Python)
• Have experience in Developer Productivity, Developer Experience, Platform Engineering, Infrastructure or Build Systems
  .
• Have built tooling for large or multi-language codebases.
• Have experience with modern CI/CD, containers and cloud infrastructure.
• Understand technologies such as Docker, Kubernetes, Infrastructure as Code and Git Hub Actions/Azure Dev Ops
  .
• Bonus: experience with AI/ML infrastructure, LLM/agent platforms, evaluation systems or regulated environments
  .
• Care deeply about developer velocity, reliability and eliminating unnecessary engineering friction.

Engineers spend their time solving difficult AI and government problems
, not configuring environments, waiting for builds or debugging infrastructure.

The result is an engineering environment where teams can move from idea to production with exceptional speed, confidence and reliability
.