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're looking for a Java engineer who builds with AI as well as with code. You'll design and build scalable, secure Java services. You'll also add AI features to those services, such as LLM-powered workflows, retrieval-augmented generation (RAG), and AI agents. And you'll use AI coding tools to speed up how the team delivers.

This role suits someone with deep backend engineering skills who has already shipped AI features to production, or is clearly on the way there. We are not looking for someone who only experiments with AI.

Primary Responsibilities:

- Core engineering
- Design, build and maintain high-performance microservices using Java 17+ and Spring Boot
- Build and use REST, GraphQL and event-driven APIs (Kafka) that are secure, observable and resilient
- Own features end to end: design, code, test, deploy and support in production
- Write clean, testable code and keep code quality and test coverage high

- AI building

- Build LLM-powered features into enterprise apps using Spring AI, Lang Chain4j or provider SDKs (Azure OpenAI, OpenAI and others)
- Design and run RAG pipelines. This covers splitting documents into chunks, building embeddings, working with vector stores (pgvector, Azure AI Search, Elasticsearch, Pinecone) and tuning how results are retrieved and ranked
- Build agent workflows that use tools and function calls, and connect them to internal systems, for example through the Model Context Protocol (MCP)
- Write, version and test prompts. Set up evaluation frameworks to measure accuracy, groundedness, latency and cost
- Build in safeguards:



PII/PHI redaction, content filters, protection against prompt injection, and human review where it's needed
- Monitor AI features in production and tune them for token use, response time and reliability

- AI-assisted engineering

- Use AI coding assistants (such as Git Hub Copilot) in daily development, testing, refactoring and documentation, and share good practices with the team
- Find chances to automate engineering work with AI, such as generating tests, triaging code reviews, and summarizing incidents

- Collaboration and leadership

- Work with product, data science, architecture and security teams to turn business problems into AI solutions
- Mentor other engineers in modern Java and AI development
- Help shape team standards for responsible AI, architecture and engineering practice

- Comply with all applicable Company policies, procedures, and business directives, changes including those relating to work location, team assignments, work schedules, and flexible work arrangements

Required Qualifications:

- Bachelor's or Master's degree in Computer Science, Engineering or a related field, or equivalent hands-on experience
- Java and backend
- 8+ years of hands-on Java work, with strong knowledge of Java 11/17+, multithreading, collections and the JVM
- Experience with microservices, REST APIs and messaging (Kafka, RabbitMQ)
- Experience with cloud platforms (AWS preferred, or Azure or GCP), Docker and Kubernetes
- Experience with CI/CD (Git Hub Actions, Jenkins, Azure Dev Ops) and test frameworks (JUnit, Mockito, Testcontainers)
- Proven solid with Spring Boot, Spring Cloud, Spring Security and JPA/Hibernate
- Proven solid with SQL and NoSQL databases (PostgreSQL, Oracle, MongoDB, Redis)

- AI skills





- Hands-on experience building apps with LLMs (GPT, Claude, Llama, Gemini or similar) through APIs
- Knowledge of responsible AI principles, data privacy and secure AI design
- Good understanding of embeddings, vector search, RAG and prompt engineering
- Understands the limits of LLMs, including hallucination, context limits, non-deterministic output and cost, and knows how to design around them
- Familiar with agent concepts: tool and function calling, planning, memory and multi-agent orchestration

Ways of working

- Proven solid problem-solving and system design skills
- Proven clear communicator who can explain AI trade-offs to people without a technical background
- Proven curious and keeps up with the quick-moving AI field

Preferred Qualifications:

- Certifications such as Azure AI Engineer Associate, AWS ML Specialty, or Oracle Java certification
- Experience with MCP servers, Copilot Studio or other agent platforms
- Experience with LLM evaluation and observability tools (Lang Smith, Langfuse, Arize, Open Telemetry)
- Experience in healthcare, with an understanding of HIPAA, PHI handling and regulated environments
- Basic ML knowledge: model fine-tuning, classic ML and NLP
- Working knowledge of Spring AI and/or Lang Chain4j. Python experience with Lang Chain or Llama Index
- Proven event-driven or reactive programming (Spring Web Flux)
- Public work: Git Hub projects, AI side projects, blog posts or talks.

At United Health 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.

📌 AI ML Engineer (India)
🏢 UnitedHealth Group
📍 India