Senior Software Engineer Developer Productivity

Senior Software Engineer – Developer Productivity

Domain: AI · Developer Infrastructure · Government Technology

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.

What You'll Do

• 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.

You May Be a Fit If You

• Have strong software engineering fundamentals and regularly write and review production code.
• 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 GitHub Actions/Azure DevOps.
• 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.

What Success Looks Like

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.