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

Posted 9 Hours Ago
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Chennai, Tamil Nadu, IND
In-Office
Senior level
Artificial Intelligence • Big Data • Healthtech • Information Technology • Machine Learning • Software • Analytics
The Role
Build, test, deploy, operate, and improve software services, APIs, applications, integrations, and automation within an AI-enabled delivery pod. Use specification-driven development and approved AI coding tools to produce secure, maintainable software while validating AI-generated output. Develop comprehensive automated tests, integrate quality and security checks into CI/CD, establish observability and resilience, collaborate with cross-functional stakeholders, and continuously improve engineering quality, delivery speed, reliability, and production support.
Summary Generated by Built In
Requisition Number: 2381464
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.
Primary Responsibilities:
  • 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 criteria, diagnose defects, perform root-cause analysis, and prevent recurrence through automation and engineering improvements
  • AI Product Delivery Expectations
    • Adopt the AIDLC as your way of working by turning approved specifications and context-rich plans into incremental, validated tasks, with accountable human review of every AI-generated output before merge or release
    • Use agent harnesses, Skills, prompts, and connectors from the Optum AI Catalog under UAIS enterprise governance, and use only enterprise-approved AI tools
    • Follow security, privacy, compliance, and responsible-AI policies, and never expose confidential, proprietary, regulated, or personal data to unapproved services
    • Use AI agents for boilerplate, refactoring, test generation, documentation, and debugging, and critically evaluate every output for correctness, security, maintainability, and alignment with product intent
    • Track the outcomes of AI-assisted work, such as cycle time, automated coverage, and escaped defects, and raise AI incidents or unreliable output through the defined channels
    • Contribute reusable prompts, patterns, and lessons learned to the AI commons so the pod can scale safe and effective AI-assisted delivery
  • Expected Impact
    • Move validated features from specification to production with fewer handoffs and less rework by working within an outcome-owning pod and automating repeatable lifecycle work
    • Improve pod delivery capacity by embedding AI-assisted planning, coding, review, test generation, documentation, and operational readiness into everyday engineering
    • Increase release confidence through continuous functional and non-functional validation, expanded automated coverage, earlier defect detection, and traceable evidence against acceptance criteria
    • Strengthen engineering consistency by applying reusable Skills, prompts, architecture guardrails, security controls, and human review of AI-generated output
  • Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Required Qualifications:
  • Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience
  • 3+ years of professional software engineering experience delivering production software
  • Experience with core engineering concepts including data structures, algorithms, object-oriented or functional design, APIs, relational and NoSQL databases, version control, and secure coding
  • Hands-on experience with automated testing across multiple test levels and with integrating validation into CI/CD workflows
  • Experience working across the development lifecycle from requirements and design through deployment, monitoring, support, and continuous improvement
  • Experience using, or a demonstrated ability to rapidly adopt, AI-assisted development tools such as agent harnesses and coding copilots (Claude Code, OpenAI Codex, or GitHub Copilot) for coding, testing, review, documentation, or troubleshooting
  • Proficiency in at least one modern programming language such as Java, Python, JavaScript/TypeScript, C#, or Go
  • Proven ability to critically evaluate AI-generated output, identify defects and unsupported assumptions, protect sensitive information, and apply human accountability before merge, promotion, or release.
  • Proven solid analytical, collaboration, and communication skills, with the ability to work effectively in a distributed, cross-functional pod.

Preferred Qualifications:
  • Experience with cloud platforms, containers, Kubernetes, infrastructure as code, microservices, event-driven architecture, or distributed systems
  • Experience with GitHub or equivalent source control, pull-request workflows, automated build and deployment platforms, observability, and production support
  • Experience with specification-driven development such as GitHub Spec-Kit, acceptance-criteria design, rapid prototyping, agile delivery, or product-oriented engineering
  • Experience applying responsible AI, security, privacy, compliance, and governance controls to AI-enabled workflows or products
  • Familiarity with generative AI, large language models, prompt engineering, retrieval-augmented generation, agentic workflows, reusable Skills and plugins, or connectors such as MCP
  • Proven evidence of improving engineering throughput, quality, reliability, reuse, or developer experience through automation and measurable continuous improvement

Success Measures
  • Shorter time to build (FCT/TTB) from approved specification to validated, deployable increment
  • Greater automated test coverage and fewer defects discovered late in the lifecycle or after release, reflected in a lower change failure rate
  • Higher quality and maintainability of AI-assisted code, tests, and technical documentation
  • Increased reuse of approved Skills, prompts, agents, and automation from the AI commons
  • Improved DORA outcomes, including deployment frequency, lead time for changes, and failed deployment recovery time, with greater production stability

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

Skills Required

  • Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or a related field, or equivalent practical experience
  • 3+ years of professional software engineering experience delivering production software
  • Knowledge of data structures, algorithms, object-oriented or functional design, APIs, relational and NoSQL databases, version control, and secure coding
  • Hands-on experience with automated testing across multiple test levels and CI/CD validation workflows
  • Experience across the software development lifecycle from requirements and design through deployment, monitoring, support, and continuous improvement
  • Experience using or rapidly adopting AI-assisted development tools such as Claude Code, OpenAI Codex, or GitHub Copilot
  • Proficiency in at least one modern programming language such as Java, Python, JavaScript, TypeScript, C#, or Go
  • Ability to critically evaluate AI-generated output, identify defects, protect sensitive information, and apply human accountability before release
  • Solid analytical, collaboration, and communication skills in a distributed, cross-functional pod
  • Experience with cloud platforms, containers, Kubernetes, infrastructure as code, microservices, event-driven architecture, or distributed systems
  • Experience with GitHub, pull-request workflows, automated build and deployment platforms, observability, and production support
  • Experience with specification-driven development such as GitHub Spec-Kit, acceptance criteria, rapid prototyping, agile delivery, or product-oriented engineering
  • Experience applying responsible AI, security, privacy, compliance, and governance controls to AI-enabled workflows or products
  • Familiarity with generative AI, large language models, prompt engineering, retrieval-augmented generation, agentic workflows, reusable Skills and plugins, or MCP connectors
  • Evidence of improving engineering throughput, quality, reliability, reuse, or developer experience through automation and measurable continuous improvement

What the Team is Saying

Optum Compensation & Benefits Highlights

  • Healthcare Strength Official materials highlight copay and HSA medical plan choices with in‑network preventive care at 100%, prescription coverage, and low/no‑cost virtual visits, plus company HSA contributions. Dental preventive services are 100% in network, and mental health resources include an EAP and premium Calm access.
  • Parental & Family Support Programs include six weeks paid parental leave, up to two weeks paid caregiver leave, and Bright Horizons back‑up care with enhanced family supports. Adoption assistance up to $10,000 for full‑time employees reinforces family‑oriented benefits.
  • Equity Value & Accessibility Financial benefits include an Employee Stock Purchase Plan at a 10% discount, expanding access to equity ownership.

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The Company
HQ: Eden Prairie, MN
160,000 Employees
Year Founded: 2011

What We Do

Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.

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Optum Offices

Hybrid Workspace

Employees engage in a combination of remote and on-site work.

Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.

Typical time on-site: Not Specified
HQEden Prairie, MN
Metro Manila, Philippines
Cebu, Philippines
Davao, Philippines
Ann Arbor, MI
Atlanta, GA
Baltimore, MD
Bengaluru, India
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Dallas, TX
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Dublin, Ireland
Hartford, CT
Houston, TX
Hyderabad, India
Jacksonville, FL
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Letterkenny, Ireland
Louisville, KY
Madison, WI
Minneapolis, MN
Nashville, TN
New Delhi, India
Philadelphia, PA
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Raleigh, NC
San Diego, CA
Washington, DC
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