1 day ago
Hyderābād, IndiaStaff+
Responsibilities
- Lead the architecture, design, implementation, and evolution of scalable, secure, resilient distributed commerce systems.
- Drive technical strategy across services, domains, and engineering teams and solve cross-organizational performance, scale, reliability, and operational challenges.
- Build AI-native systems using Generative AI, LLMs, RAG architectures, vector databases, orchestration frameworks, and AI agents.
- Establish AI evaluation, quality, observability, governance, safety, and human-in-the-loop engineering practices.
- Drive engineering excellence across architecture, development, testing, deployment, operations, reliability, security, privacy, and compliance.
- Lead production root-cause investigations and systemic fixes.
- Influence architecture and design decisions across organizations, lead technical reviews and architecture boards, mentor senior and principal engineers, and advise technical and business leaders.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- 10+ years of professional software engineering experience building large-scale production systems.
- Experience serving as a technical lead or architecture owner for complex enterprise-scale platforms and delivering business-critical systems reliably at scale.
- Expertise in one or more of C#, Java, Python, Go, or C++.
- Strong knowledge of software architecture, API design, microservices, event-driven architectures, distributed systems, cloud-native services, containers, Kubernetes, service meshes, resiliency, observability, and reliability engineering.
- Experience with relational and NoSQL systems, SQL performance optimization, large-scale data processing, streaming platforms, analytics systems, and high-performance transactional systems.
- Ability to work across the technology stack, including modern web applications, services, frontend frameworks, backend systems, APIs, platforms, and data engineering.
- Deep technical understanding of Generative AI, LLMs, agentic AI, RAG, prompt engineering, AI observability and evaluation, AI safety and governance, orchestration platforms, vector search, AI-assisted development, and human-in-the-loop architectures.
- Preferred qualifications include a master’s degree or PhD, AI-first production product experience, commerce or financial-systems experience, significant open-source contributions, publications, patents, recognized technical thought leadership, and experience working across geographically distributed engineering teams.
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About Microsoft
Every company has a mission. What's ours? To empower every person and every organization to achieve more. We believe technology can and should be a force for good and that meaningful innovation contributes to a brighter world in the future and today. Our culture doesn’t just encourage curiosity; it embraces it. Each day we make progress together by showing up as our authentic selves. We show up with a learn-it-all mentality. We show up cheering on others, knowing their success doesn't diminish our own. We show up every day open to learning our own biases, changing our behavior, and inviting in differences. Because impact matters. Microsoft operates in 190 countries and is made up of approximately 228,000 passionate employees worldwide.