Software Engineer II & Senior Software Engineer

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Software Engineering

The role focuses on building and scaling backend services and data pipelines that power device and security intelligence within Microsoft Defender for Endpoint. The core responsibility is to transform fragmented signals into a consistent, reliable data foundation that supports downstream systems, customers, and AI-driven capabilities. This involves designing, building, and scaling these systems, defining data models and pipelines, and contributing to architectural decisions for correctness, scalability, and durability.

What you'd actually do

  1. Design, build, and scale backend services and data pipelines that power device and security intelligence
  2. Contribute to the development of high-quality, durable data foundations used across Microsoft Security
  3. Bring together fragmented device and security signals from multiple systems into a consistent, reliable view
  4. Define and implement data models, pipelines, and system contracts across large-scale distributed systems
  5. Contribute to architectural decisions and tradeoffs that balance correctness, scalability, latency, and complexity

Skills

Required

  • Bachelor's Degree in Computer Science or related technical field AND 2+ 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

  • 5+ years of experience building and shipping backend services or data platforms
  • Experience designing and owning distributed systems at scale
  • Proven fundamentals in system design, data modeling, and service architecture
  • Experience working with Azure or large-scale cloud environments
  • Ability to drive clarity and execution in ambiguous problem spaces
  • Interest in security, platform engineering, or AI-driven systems

What the JD emphasized

  • building systems that others rely on
  • correct, scalable, and durable
  • evolving and sometimes ambiguous problem spaces
  • transforming fragmented signals
  • clean, consistent, and trustworthy data foundation
  • AI can depend on
  • security screening requirements

Other signals

  • building foundational backend services and data platforms
  • transforming fragmented signals into a clean, consistent, and trustworthy data foundation
  • powering analytics, reporting, automation, and AI-driven insights