Navin Narra

About Navin Narra

I bring ~18 years of experience designing and operating large-scale backend and cloud-native systems at Microsoft, with a strong focus on AI infrastructure, model deployment, and AI-powered product platforms. Over the last several years, my work has centered on taking AI from research to reliable production — building the systems that make models servable, scalable, observable, and cost-efficient in real-world products used by millions. What I specialize in: • AI inference platforms (AKS, ONNX, real-time services) • ML systems & MLOps (training pipelines, evaluation, deployment, rollout) • AI-enabled product backends (copilots, insights, assistive experiences) • Cloud-native architecture, reliability, and operational excellence • Enabling other teams to safely and effectively ship AI features I have worked across Xbox Gaming AI, Windows AI, Power Apps, Azure Data, and Microsoft’s Office of the CTO, contributing to AI systems spanning consumer products, developer platforms, and enterprise services. I have led and grown engineering teams while remaining deeply engaged in architecture and technical execution, and I’m comfortable contributing as a senior technical leader or in broader engineering leadership roles where I can create meaningful impact. I am focused on opportunities where I can help organizations take AI from early experimentation to production-grade platforms — particularly in roles centered on AI infrastructure, ML systems, and applied AI engineering at scale.

Experience

1. Software Engineer Xbox Gaming Ai

   Microsoft

   Nov 2024 — Present

   Built and operated cloud-native backend systems powering AI features across Xbox, including game assistance and copilot-style experiences. Designed the inference infrastructure and service architecture enabling safe, scalable integration of AI capabilities into core Xbox experiences. Focused on production-critical aspects of AI systems, including- Secure model deployment and controlled rollout strategies - Service reliability, observability, and performance optimization - Security, compliance, and responsible handling of user data - Operational readiness for high-availability, globally deployed services Partnered closely with ML, product, and platform teams to translate research outputs into scalable, production-grade AI infrastructure.

Education

• University of Washington

  Certificate

• University of Mumbai

  B.E

• Boston University

  Masters

Skills

• Distributed Systems
• Software Development
• Software Engineering
• Algorithms
• Requirements Analysis
• Agile Methodologies