Senior Software Engineer - Java/.net/python/go, API development, gen AI - Chennai, Bangalore

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together. We are seeking a Software Engineer to join an AI-enabled delivery pod within DMS in OGA India and help deliver software through the AI Product Delivery Lifecycle (AIDLC), Optum Technology's standard way of working in which AI drives the flow while engineers own the outcomes. You will apply strong software engineering fundamentals across the five AIDLC phases (Portfolio Discovery, Inception, Construction, Readiness, and Operations), using enterprise-approved agent harnesses, reusable Skills, and prompts from the Optum AI Catalog to produce secure, maintainable, production-ready software. As a Builder in a small, cross-functional pod of three to five people, you are accountable not only for creating software but also for validating AI-generated output, engineering quality into every increment, and converting well-defined product intent into measurable customer and business outcomes.

Contribute as a Builder in a small, cross-functional, AI-enabled delivery pod that owns outcomes end to end, working closely with the Product, Quality, and Operations pod roles Design, build, test, deploy, operate, and continuously improve software services, APIs, applications, data integrations, and automation across the Construction, Readiness, and Operations phases Use AIDLC and GitHub Spec-Kit spec-driven development (Specify, Plan, Tasks, Implement) to translate approved specifications into decomposed tasks, implementation artifacts, tests, documentation, and release-ready increments Direct enterprise-approved AI coding agents and copilots such as Claude Code, OpenAI Codex, and GitHub Copilot with clear prompts and AGENTS.md guardrails to generate and refine code and tests, and validate every output for correctness, maintainability, performance, security, accessibility, and alignment with product intent Partner with product, architecture, data, security, and operations stakeholders to clarify requirements, define acceptance criteria, identify dependencies, and resolve delivery risks early Participate in design and code reviews, pair programming, frequent demonstrations, incident learning, and retrospectives, including AI retrospectives, and contribute reusable patterns, prompts, and lessons learned back to the AI commons Build observability, resilience, deployment automation, and supportability into solutions, and use production feedback to improve quality and delivery flow Quality Engineering and Testing Own quality as part of software engineering work, and build and test concurrently within the pod rather than relying on downstream quality handoffs Create, review, execute, and maintain unit, component, API, integration, contract, end-to-end, regression, and acceptance tests appropriate to the solution Define and validate non-functional requirements, including performance, scalability, reliability, resiliency, security, accessibility, privacy, and operability. Use AI-assisted test generation, coverage-gap analysis, defect detection, test-data creation, and failure analysis while applying human judgment to verify scenarios, edge cases, expected results, and risk coverage Integrate automated tests, static analysis, dependency and security scans, quality gates, and deployment checks into CI/CD pipelines so validation is continuous and release is a low-risk, evidence-based event Trace tests and validation evidence to requirements and acceptance