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 looking for an experienced AI Engineer to design, build, and deploy enterprise-grade AI solutions, with a solid focus on Agentic AI, Retrieval-Augmented Generation (RAG), AI workflow automation, and intelligent application development. The ideal candidate should have hands-on experience building production-ready AI systems using frameworks such as Spring AI, LangChain, LangGraph, and cloud platforms including AWS and Azure.
The role requires a solid engineering mindset, practical experience with LLM-based application development, and the ability to translate business problems into scalable AI-powered solutions.
Primary Responsibilities:
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Design, develop, and deploy Agentic AI solutions using LLMs, tools, memory, orchestration, and multi-step reasoning workflows
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Build and maintain RAG-based applications using vector databases, embeddings, document ingestion pipelines, retrieval strategies, and prompt engineering
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Develop AI-powered workflow automation solutions to improve operational efficiency and business process intelligence
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Work with frameworks such as Spring AI, LangChain, LangGraph, and related AI orchestration tools
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Integrate AI capabilities into enterprise applications, APIs, microservices, and cloud-native platforms
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Build scalable backend services using Java/Spring Boot and/or Python-based AI frameworks
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Implement prompt engineering, evaluation, guardrails, observability, and monitoring for AI applications
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Work with cloud services on AWS and Azure, including AI/ML services, storage, compute, serverless, containerization, and deployment pipelines
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Implement observability and monitoring for application health, AI workflow performance, model behavior, latency, failures, and usage patterns
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Collaborate with product owners, architects, data engineers, and business stakeholders to understand requirements and deliver AI solutions
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Evaluate emerging AI technologies, LLM providers, model APIs, and open-source frameworks for enterprise adoption
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Ensure AI solutions follow security, compliance, privacy, and responsible AI best practices
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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:
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Graduate degree or equivalent experience
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Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or a related field, or equivalent practical experience
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5+ years of overall software engineering experience
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Hands-on experience building AI/ML, GenAI, or LLM-based applications
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Solid experience with Agentic AI concepts, including tool calling, planning, memory, multi-agent workflows, and autonomous task execution
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Practical experience with RAG architecture, including embeddings, chunking, retrieval, re-ranking, vector search, and document processing
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Experience with Spring AI, LangChain, and LangGraph
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Experience integrating LLMs such as OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock, or open-source models
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Experience with Git, CI/CD pipelines, Docker, Kubernetes, and modern DevOps practices
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Experience with Azure OpenAI, AWS Bedrock, SageMaker, Azure AI Foundry, Azure AI Search, or similar cloud-native AI services
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Experience with observability and monitoring tools such as Splunk, Dynatrace, Amazon CloudWatch, Azure Monitor, and Azure Log Analytics
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Experience with workflow orchestration tools, message queues, or automation platforms
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Cloud experience with AWS and Azure, including services related to AI, compute, storage, APIs, containers, and CI/CD
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Knowledge of vector databases such as Pinecone, Weaviate, Milvus, Chroma, FAISS, OpenSearch, or Azure AI Search
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Knowledge of LLM evaluation, hallucination reduction, grounding, tracing, and observability tools
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Understanding of responsible AI, data privacy, access control, and compliance requirements
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Good understanding of REST APIs, microservices, event-driven architecture, and enterprise integration patterns
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Familiarity with security and governance practices for GenAI applications
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Demonstrated solid programming skills in Java/Spring Boot and/or Python
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Demonstrated solid problem-solving skills and ability to build reliable, maintainable, production-grade systems
Preferred Qualifications:
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AWS, Azure AI Engineer, Kubernetes, DevOps, or cloud architecture certifications
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Knowledge of the US Healthcare domain
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.
