Senior Software Engineer

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

Senior Software Engineer role focused on building and integrating customer-facing, high-performance, low-latency, and high-availability AI services within the Responsible AI group at Microsoft. The role involves AI-native development, coding, system design, and ensuring engineering excellence for AI services, with a strong emphasis on reliability, supportability, and compliance.

What you'd actually do

  1. AI-Native Development: Use AI tools responsibly and consistently across the SDLC, own the accuracy of AI-generated artifacts, and improve AI-enabled processes using engineering-health measures (Accelerate/SPACE/ESSP) through ongoing experimentation.
  2. Coding: Raise code quality through timely, high-signal reviews and strong engineering practices (secure/performance/testability/diagnosability), using automated analysis plus disciplined debugging/telemetry and retrospectives to prevent recurrence.
  3. Design: Own and evolve architecture/design for complex scenarios with clear test strategy and security testing, integrate dependencies across systems/teams, evaluate tradeoffs/options, and ensure solutions meet performance, scalability, resiliency/DR, COGS, and compliance requirements.
  4. Engineering Excellence: Drive engineering best practices and automation (toward zero-touch), strengthen security/privacy/accessibility compliance with auditable evidence, build/extend developer tools, stay current on trends, and operationalize “security as code” with gates/scanners/monitoring.
  5. Implement: Plan and deliver through roadmaps and capacity-aware execution with flighting/experimentation and success + guardrail metrics, while using safe deployment practices, secure rollouts, dependency hygiene, and well-defined rollback strategies.

Skills

Required

  • Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 6+ years of professional software engineering experience
  • strong hands‑on development in one or more programming languages such as C#, Python.
  • Strong expertise in software design and development, including system architecture, data structures, algorithms, and designing scalable, reliable, and secure services.
  • Proven experience owning and delivering complex features or services end‑to‑end, from design through implementation, testing, deployment, and operational support.
  • Solid understanding of cloud‑based and distributed systems, including reliability, performance optimization, telemetry, diagnostics, and live site support considerations.
  • Ability to influence technical direction and mentor others, demonstrated through design leadership, code reviews, and collaboration across teams.
  • Experience applying secure coding practices and compliance requirements, ensuring solutions meet Microsoft’s security, privacy, and engineering quality standards.
  • Communicating to Drive Mutual Success: Articulating messaging in a clear and respectful manner to achieve collaborative and mutually beneficial outcomes while ensuring all parties are heard, understood, and aligned towards shared goals.
  • Designing and Architecting Business Solutions: Designing and architecting products, services, and systems by employing design principles across diverse technological solutions and guiding projects through each phase of the engineering lifecycle to ensure alignment with business goals and customer satisfaction.
  • Driving Solution Improvement and Excellence: Leading the validation of innovative products, services, and solutions through pinpointing opportunities for improvement, monitoring and testing systems, and fostering strategic solutions to identified challenges or issues.
  • Engineering Robust Software Solutions: Employing computer science principles to design, develop, and optimize scalable algorithms, distributed systems, business applications, and other software solutions.
  • Enhancing Product and Project Execution: Streamlining project lifecycles through the integration of project and product planning and quality assurance methods to ensure all phases of a project are planned, assessed, and aligned with strategic goals and to optimize performance and project outcomes.
  • Solving Problems Through a Data-Driven Approach: Extracting actionable insights to understand their implications within the bro

What the JD emphasized

  • own the accuracy of AI-generated artifacts
  • high performance
  • low latency
  • high availability
  • security testing
  • security/privacy/accessibility compliance
  • secure deployment practices
  • privacy-aware monitoring

Other signals

  • Responsible AI
  • customer-facing AI services
  • low latency
  • high availability
  • build new AI services
  • integrate with existing services