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.
Primary Responsibilities:
- Design, develop, and deploy Agentic AI solutions using LLMs, tools, memory, orchestration, and multi-step reasoning workflows
- Build and maintain RAG-based applications using vector databases, embeddings, document ingestion pipelines, retrieval strategies, and prompt engineering
- Develop AI-powered workflow automation solutions to improve operational efficiency and business process intelligence
- Work with frameworks such as Spring AI, LangChain, LangGraph, and related AI orchestration tools
- Integrate AI capabilities into enterprise applications, APIs, microservices, and cloud-native platforms
- Build scalable backend services using Java/Spring Boot and/or Python-based AI frameworks
- Implement prompt engineering, evaluation, guardrails, observability, and monitoring for AI applications
- Work with cloud services on AWS and/or Azure, including AI/ML services, storage, compute, serverless, containerization, and deployment pipelines
- Collaborate with product owners, architects, data engineers, and business stakeholders to understand requirements and deliver AI solutions
- Explore and evaluate emerging AI tools, LLM providers, model APIs, and open-source frameworks
- Ensure AI solutions follow security, compliance, privacy, and responsible-AI best practices
- 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 or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or a related field
- 3+ years of software engineering experience, with hands-on work building AI/GenAI or LLM-based applications (e.g., agentic solutions, RAG systems, or AI chatbots)
- Practical experience integrating LLMs via APIs (e.g., OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock, or open-source models)
- Working experience with at least one GenAI framework such as Spring AI, LangChain, or LangGraph
- Experience using at least one vector database (e.g., Pinecone, Weaviate, Milvus, Chroma, FAISS, OpenSearch, or Azure AI Search)
- Hands-on cloud experience with AWS or Azure (compute, storage, and AI/ML services)
- Solid programming skills in Java/Spring Boot and/or Python
- Understanding of RAG fundamentals: embeddings, chunking, retrieval, vector search, and prompt engineering
- Working knowledge of agentic concepts: tool/function calling, orchestration, memory, and multi-step reasoning workflows
- Solid understanding of REST APIs and microservices
- Familiarity with Git, CI/CD pipelines, and Docker
- Proven solid problem-solving skills and the ability to build reliable, maintainable, production-grade systems
- Awareness of security, privacy, and responsible-AI practices when building AI applications
Preferred Qualifications:
- Experience with additional cloud-native AI services such as Azure OpenAI, AWS Bedrock, SageMaker, Azure AI Foundry, or Azure AI Search
- Experience working across both AWS and Azure
- Experience building AI solutions for business use cases such as enterprise search, document intelligence, customer support, operations, or developer productivity
- Experience with Kubernetes and container orchestration
- Experience with workflow orchestration tools or automation platforms
- Exposure to model fine-tuning, prompt evaluation frameworks, or synthetic data generation
- Advanced RAG techniques such as re-ranking, hybrid search, and advanced document ingestion pipelines
- Multi-agent workflows and autonomous task execution
- Knowledge of LLM evaluation, hallucination reduction, grounding, tracing, and guardrails
- Knowledge of observability tools (e.g., Splunk, Dynatrace, Amazon CloudWatch, Azure Loginsights) for monitoring applications and AI systems
- Familiarity with event-driven architecture, message queues, and enterprise integration patterns
- Familiarity with governance, access control, and compliance requirements for GenAI applications
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.