Build and evolve distributed services that underpin massive training runs Improve iteration loops for researchers and engineers Apply advanced performance optimization techniques that directly impact product quality and operational excellence Develop deep expertise in ML systems, AI infrastructure, and compute orchestration AI-Native Development Independently uses appropriate artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC) in a disciplined manner. Takes responsibility for the content of their AI-generated requirements, design documents, code, and other assets, assisting other members of the team to do the same. Uses SDLC and engineering health measures (e.g., Accelerate, SPACE framework, Engineering System Success Playbook [ESSP]) to improve processes and practices, especially those involving AI. Experiments with AI tools and practices to improve their own capabilities. Coding Leads by example within the team to produce extensible, maintainable, well-tested, secure, and performant code that adheres to design specifications. Continuously improves code performance, testability, maintainability, effectiveness, and cost, while learning about and accounting for relevant trade-offs. Applies metrics to drive code quality and stability. Applies appropriate coding patterns and best practices (e.g., leveraging state-of-the-art generative artificial intelligence [GenAI], approaches to source code organization, naming conventions). Identifies and escalates blockers or unknowns during the development process, communicates how they will impact timelines, and identifies strategies and/or opportunities to address them. Design Leads discussions for and owns the architecture of a products/solutions and creates proposals for architecture by testing design hypotheses and develop complex design specifications. Tests and explores various design options for a complex product/solution scenario, outlining strengths and weaknesses of each option. Independently collaborates with architects to build and modify complex products/solutions, providing feedback as needed. Owns or collaborates with other engineers on the architecture of solutions, with minimal technical oversight. Develops design documents that support user stories and other product requirements.



Maintains awareness of the current technology landscape, and determines how to integrate these technologies within existing systems. Shares learnings and identified solutions from investigations with the team and owns for some design decisions. Ensures system architecture and individual designs meet performance, scalability, resiliency, cost of goods sold (COGS), disaster recovery, and other requirements and expectations. Understands and coaches less experienced engineers on the importance of building solutions that expand upon the work of others. Drives the refinement of products through data analytics, and makes informed decisions in engineering products through data integration. Reviews designs/architectures within and across teams to provide recommendations for improvements. Engineering Excellence Applies best practices to build code based on well-established methods and secure design principles while also applying best practices for new code development and formal validation of security invariants. Drives product development and scaling to customer requirements and applies best practices for meeting scaling needs and performance expectations and security promises. Implement Leverages their subject-matter expertise to partner with appropriate stakeholders (e.g., technical program managers) to drive a workgroup's project plans, release plans, and work items. Organizes work into smaller sets of tasks as part of an overall roadmap. Guides other members for project estimation and escalates issues that might cause a delay. Ensures required security protections and detection processes are accounted for in planning. Ensures project plans adhere to security, privacy, and compliance requirements. Ensures all code for a product/solution is properly flighted for quicker mitigation of production incidents. Calculates capacity for planning,



accounting for appropriate failover and backup/restore mechanisms for disaster recovery for a project/sub-system of a product. Makes considerations for productive operation of a project/sub-system of a product after it is live. Establishes a rollback plan for a project/sub-system of a product. Reliability and Supportability Maintains operations of live site service, following security best practices when responding quickly to mitigate issues while using the minimum required permissions to do so that arise on a rotational, on-call basis. Implements solutions and mitigations to more complex issues impacting performance or functionality of live site service and escalates appropriately. Reviews and writes incident postmortem and presents insights that drive changes to reduce or eliminate incidents. Independently improves troubleshooting guides (TSGs), wikis, tests, and telemetry to make on-call better, and recommends user-facing support documentation and additional test coverage to reduce likelihood of future user-initiated incidents. Enables secure operations, security monitoring, and integration with live site investigation activities. Identifies and proposes opportunities (e.g., lunch talks, automation, practices, tools) that can be leveraged to improve the live site experience. Adds comprehensive observability and monitoring to services. Bachelor's Degree in Computer Science, or Computer Engineering, or related field AND 8+ years related software engineering experience OR Master's Degree in Computer Science, or Computer Engineering, or related field AND 5+ years related software engineering experience OR equivalent experience Proficiency in programming languages & tools such as .Net, Java, Azure functions, Docker, Python Experience delivering large scale, distributed, cloud based software services Passion for machine learning, artificial intelligence, and data science Ability to work collaboratively in a team and communicate complex concepts effectively Experience with day-to-day AI agents and tool use Proficiency in Agile development practices and Continuous Integration/Continuous Deployment (CI/CD) Quick learner with a passion for solving complex and exciting problems. Experience with AI/ML internals a big plus Experience with Azure is a plus

📌 Senior Software Engineer (Bengaluru)
🏢 Microsoft
📍 Bengaluru