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Microsoft

Principal Software Engineer (AI / Agentic Developer Productivity)

United States, Washington, RedmondSenior individual contributorSoftware Engineering

Listed on Microsoft’s official careers site. Posted July 20, 2026. Check that it is still open and apply there.

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Job description

Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing. Use AI in your daily coding and advocate to the team and customers an evolving state-of-the-art of how best to do this. Demonstrate resiliency to experiment and try multiple AI approaches that may not work — because no one has tried them before. Provide mentorship and coaching to engineers in, and beyond, your team.

Write and review clean, well-thought-out code with an emphasis on quality, performance, simplicity, durability, scalability, and maintainability. Contribute positively to a culture where everyone can bring their full and authentic self and where we do our best work as a result. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

These requirements include but are not limited to the following specialized security screenings: Prior experience building with Agent SDKs, large language models (LLMs), prompt engineering, or AI orchestration frameworks (e.g., LangChain, Semantic Kernel, AutoGen, LlamaIndex, or similar). Familiarity with agentic AI development patterns — multi-step reasoning, tool/function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows.

Proven experience as a Software Engineer delivering large-scale, production-quality systems.

Solid software engineering fundamentals

system design, algorithms, testing, debugging, and code review. Demonstrated ability to lead technical direction and mentor peers in a collaborative team environment. Comfort working in ambiguous, fast-moving problem spaces where best practices are still being established. Hands-on experience with AI-powered developer tooling and coding assistants, such as: GitHub Copilot and Copilot Workspace — AI pair programming, CLI, and task-oriented development Claude Code — agentic CLI for autonomous software engineering tasks OpenAI Codex / ChatGPT — LLM-based code generation and explanation Cursor — AI-native code editor with inline generation and multi-file edits Prior experience using agentic plugins, agents, skills, hooks, etc.

Experience dogfooding, evaluating, and forming opinions on emerging AI developer tools, and translating those insights into team-wide best practices. Background in developer tooling, build systems, CI/CD pipelines, or engineering systems at scale.

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