Senior Software Engineer, Foundry Agents - Coreai

Microsoft Microsoft · Big Tech · Redmond, WA +2 · Software Engineering

Senior Software Engineer role focused on building and evolving large-scale, cloud-native systems for the end-to-end lifecycle of intelligent agents. This includes secure enterprise deployment, governed tool integration, model fine-tuning, training workflows, and production observability, evaluation, and optimization.

What you'd actually do

  1. Build and scale services that support secure agent deployment and execution, governed tool integration, training/fine‑tuning, and observability/evaluation
  2. Design and implement distributed systems and cloud services to run agents reliably at enterprise scale
  3. Improve developer and researcher workflows through better tooling, abstractions, and automation across fine‑tuning, evaluation, and optimization
  4. Debug and optimize interactions across models, data, and infrastructure
  5. Contribute to technical design and implementation across the software development lifecycle

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
  • Ability to meet Microsoft, customer and/or government security screening requirements

Nice to have

  • Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • 5+ years technical engineering experience designing and delivering highly available, large-scale cloud services and distributed systems
  • 3+ years of technical engineering experience with machine learning or Artificial Intelligence (AI) systems

What the JD emphasized

  • secure agent deployment
  • governed tool integration
  • fine-tuning
  • training
  • observability
  • evaluation
  • optimization
  • enterprise scale
  • distributed systems
  • cloud services
  • highly available, large-scale cloud services and distributed systems
  • machine learning or Artificial Intelligence (AI) systems

Other signals

  • agent lifecycle
  • enterprise scale
  • governed tools
  • fine-tuning
  • observability
  • evaluation
  • optimization