Senior Software Engineer

Microsoft Microsoft · Big Tech · Bengaluru, KA, IN · Software Engineering

Senior Software Engineer role focused on designing and building secure, scalable platform solutions for Identity and Access Management (IAM) within Microsoft's Cloud & AI organization. The role emphasizes an AI-first approach, leveraging AI-assisted tooling, intent detection, knowledge grounding, orchestration, and policy-driven workflows to address security challenges and enable customer self-resolution. The engineer will work on production services and distributed systems, with a preference for those who have built large, extensible, and scalable systems, and experience with cloud platforms like Azure.

What you'd actually do

  1. Work on Identity and Access Management (IAM) platforms and internal identity systems to design and implement features that improve security posture, operational reliability, and customer experience.
  2. Design & develop Secure / Scalable internal platform(s) and service(s) that educate, proactively address recurring customer issues and enable customer self‑resolution through intelligent, guided experiences.
  3. Apply an AI‑first approach to problem solving—leveraging intent detection, knowledge grounding, orchestration, and policy‑driven workflows before introducing traditional code‑heavy automation.
  4. Proactively identify gaps, risks, and improvement opportunities in existing internal IAM systems, and drive design and implementation of enhancements aligned with security, scalability, and long‑term maintainability.
  5. Mentor junior engineers through design reviews, code reviews, and technical guidance, helping raise overall team engineering quality and security awareness

Skills

Required

  • software engineering
  • data structures
  • algorithms
  • object-oriented or modular design
  • production services or distributed systems
  • API-based system integration
  • secure service-to-service communication
  • cloud platform (Azure preferred)

Nice to have

  • Identity & Access Management domain
  • security platforms
  • reducing operational toil through automation-first or intelligence driven system design
  • influence architectural decisions
  • applying AI techniques in production systems (e.g anomaly detection, LLM backed workflows)

What the JD emphasized

  • designing and building extensible, secure, and scalable platform solutions
  • reusable, composable foundations
  • AI‑first approach
  • production services or distributed systems

Other signals

  • AI-first approach to problem solving
  • leveraging intent detection, knowledge grounding, orchestration, and policy-driven workflows
  • AI-assisted tooling may be leveraged to enhance engineering productivity and system intelligence