Software Engineer

Microsoft Microsoft · Big Tech · Vancouver, BC +1 · Software Engineering

Software Engineer role focused on building an agentic engineering platform for AI-powered productivity across Microsoft's codebases, involving AI models and orchestration frameworks.

What you'd actually do

  1. Own and deliver features across the software development lifecycle, including design, architecture, implementation, testing, debugging, release, and ongoing support.
  2. Apply AI-assisted development tools and practices in daily workflows, and share approaches with team members and partner teams.
  3. Explore and evaluate multiple AI-assisted development approaches to improve engineering workflows and outcomes.
  4. Provide mentorship and guidance to engineers within and across teams.
  5. Write and review high-quality code with a focus on performance, reliability, scalability, and maintainability.

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.

Nice to have

  • Strong software engineering fundamentals, including system design, algorithms, testing, debugging, and code review.
  • Demonstrated ability to lead technical direction and mentor peers in a collaborative team environment.
  • Comfortable working in ambiguous, fast-moving problem spaces where best practices are still emerging.
  • Hands-on experience with AI-powered developer tooling and coding assistants, such as: GitHub Copilot and Copilot Workspace, Claude Code, OpenAI Codex / ChatGPT, Cursor
  • Experience with agentic tooling concepts such as plugins, agents, skills, or hooks.
  • 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, including multi-step reasoning, tool/function calling, retrieval-augmented generation (RAG), and human-in-the-loop workflows.
  • Experience evaluating and using emerging AI developer tools, and translating insights into team-wide best practices.
  • Background in developer tooling, build systems, CI/CD pipelines, or engineering systems at scale.

What the JD emphasized

  • Comfortable working in ambiguous, fast-moving problem spaces where best practices are still emerging.

Other signals

  • agentic engineering platform
  • AI-powered productivity
  • AI-assisted code understanding and modification
  • AI models and orchestration frameworks