Senior Software Engineer - Search

Microsoft Microsoft · Big Tech · Hyderabad, TS, IN · Software Engineering

Senior Software Engineer to design and deliver platform-level search and AI Platform capabilities for Windows. The role involves building the next-generation search that powers File Explorer, Universal Search, Copilot, and future LLM integrations, as well as the Windows AI Platform for developers. Responsibilities include designing and implementing core search components, driving technical deep-dives, owning end-to-end feature delivery, building observability infrastructure, and championing AI-assisted engineering practices.

What you'd actually do

  1. Designing and implementing core components of the Windows Search Platform.
  2. Driving technical deep-dives and authoring design specifications for complex features, establishing yourself as a technical authority on the search platform stack.
  3. Owning end-to-end delivery of features from design through coding, testing, self-host validation, and retail rollout — with a strong focus on quality, reliability, and performance.
  4. Collaborating cross-functionally with Products and Data teams to drive technical alignment and resolve architectural trade-offs.
  5. Building and maintaining observability infrastructure.

Skills

Required

  • Bachelor'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.
  • Solid proficiency in C/C++ with experience in systems-level or platform software development.
  • Experience with multi-threaded programming, memory management, and performance optimization in native code.
  • Demonstrated ability to own and deliver complex features end-to-end with minimal guidance.

Nice to have

  • Master's Degree in Computer Science or related technical field AND 7+ years technical engineering experience.
  • OR Bachelor's Degree AND 8+ years technical engineering experience.
  • OR equivalent experience.
  • Deep understanding of Windows internals, NT kernel, file systems (NTFS/ReFS), or OS-level services and infrastructure.
  • Experience with search/indexing systems, database internals, query processing, or information retrieval at scale.
  • Track record of authoring design specifications and driving technical consensus across multiple stakeholders.
  • Experience with telemetry frameworks, observability pipelines, and data-driven quality engineering.
  • Familiarity with AI/ML integration patterns — embedding-based retrieval, LLM consumption APIs, or AI-native platform design.
  • Solid debugging and root-cause analysis skills across user-mode and kernel-mode components.
  • Methodical analytical skills with a systematic approach to software design, testing, and performance analysis.
  • Confident communicator who can articulate technical decisions and trade-offs to both engineering peers and leadership.
  • Self-motivated with a strong sense of ownership, accountability, and a bias toward action and speed.

What the JD emphasized

  • core components of the Windows Search Platform
  • AI-powered Search Platform
  • Windows AI Platform
  • AI-assisted software development
  • systems-level programming
  • platform architecture
  • complex technical challenges
  • end-to-end delivery
  • quality, reliability, and performance
  • observability infrastructure
  • Reliability and Quality
  • AI-assisted engineering practices
  • technical debt, performance bottlenecks, and reliability risks
  • systems-level or platform software development
  • multi-threaded programming, memory management, and performance optimization
  • own and deliver complex features end-to-end
  • Windows internals, NT kernel, file systems (NTFS/ReFS), or OS-level services and infrastructure
  • search/indexing systems, database internals, query processing, or information retrieval at scale
  • telemetry frameworks, observability pipelines, and data-driven quality engineering
  • embedding-based retrieval, LLM consumption APIs, or AI-native platform design
  • user-mode and kernel-mode components
  • systematic approach to software design, testing, and performance analysis

Other signals

  • AI-powered Search Platform
  • Windows AI Platform
  • Copilot and future MCP/LLM integrations
  • AI-assisted software development