Senior Manager Software Engineering

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 Sr Mgr, Software Engineering to lead DMS engineering teams in OGA India through the shift from traditional software delivery to an AI-Driven Development Life Cycle (AIDLC). This leader will combine people leadership, hands-on engineering depth, and end-to-end delivery accountability to embed governed AI into discovery, specification, architecture, development, testing, release readiness, operations, and continuous improvement. The role will accelerate strategic roadmap capabilities by reducing handoffs and rework, increasing delivery throughput, strengthening quality and production stability, and building durable AI engineering capability across the team.

Lead AI-driven software delivery: establish AIDLC practices across portfolio discovery, inception, construction, readiness, and operations, and ensure AI accelerates execution while engineers retain accountability for design trade-offs, validation, risk acceptance, and outcomes Accelerate the roadmap: translate strategic priorities into clear specifications, prototypes, buildable and testable work units, and production increments, and remove delivery constraints and shorten time from opportunity to measurable value Strengthen engineering excellence: set standards for architecture, secure coding, code review, observability, CI/CD, infrastructure as code, operational readiness, documentation, reliability, and cost-conscious engineering across modern cloud-native platforms Manage outcomes with evidence: establish baseline and ongoing measures for lead time, throughput, deployment frequency, escaped defects, change failure rate, recovery time, automated test coverage, reliability, adoption, and capacity trends, and use the data to inspect, adapt, and demonstrate business impact Develop engineering talent: hire, coach, and grow software and AI engineering talent, raise proficiency in specifications, prompting, agentic workflows, architecture, testing, DevSecOps, and production ownership, and create reusable practices that improve delivery capabilities beyond a single team Lead cross-functional execution: partner with product, architecture, quality, security, data, infrastructure, operations, and business stakeholders to align priorities, resolve dependencies, manage risks, and maintain end-to-end ownership Champion reuse and continuous improvement: promote reusable specifications, prompts, skills, agents, test assets, platform components, and engineering patterns to reduce duplicate work and compound delivery gains across OGA Quality Engineering and Testing Build quality into the lifecycle: define a shift-left testing strategy spanning unit, integration, API, contract, UI, regression, accessibility, performance, resilience, security, data, and production validation, and make testability, traceability, and release evidence part of architecture and delivery decisions Scale AI-assisted testing: lead adoption of AI-generated, human-reviewed test plans, test data, automation, coverage-gap analysis, defect triage, and regression suites to improve defect prevention, release confidence, and feedback speed Set organization-standard quality gates and release-evidence requirements, and hold teams accountable for functional and non-functional coverage across performance, security, resilience, accessibility, and data quality Use quality signals such as escaped defects, change