Key skills
Prompt EngineeringRetrieval-Augmented Generation (RAG)Agentic AIPythonPySparkT-SQLSQLHadoopSparkStatisticsData ModelingSimulationGenerative AI frameworksLangChainHuggingFaceOpenAI APIsAzure DatabricksAzure ML StudioAWS BedrockAzure FoundryKafkaGoogle Cloud PlatformCloud-native AI servicesCI/CD pipelinesGitHub ActionsContainerizationLLM securityResponsible AI practicesLarge Language Models (LLMs)GPTGeminiLLaMATensorFlowDeep learning architecturesCNNsAutoencodersAgile methodologiesDevOps practicesData warehousingSnowflakeMLFlowDockerFlaskLangGraphREST APIsSDKsMLOpsAIMLDeep LearningNLPGenerative AIGenAILLMOpenAILlamaRAGAgenticPandasMLflowData WarehousingData LakeAnalyticsDatabricksAWSAzureGCPBedrockGitGitHubAgileCI/CD
About this role
Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. We are seeking a highly skilled and motivated AI/ML Engineer to lead innovations in claims adjudication through advanced Generative AI solutions, designing and deploying secure, scalable AI systems that deliver measurable impact.
Responsibilities:
- Design, develop, and deploy AI/ML and Generative AI models for predictive, prescriptive, and generative analytics across healthcare datasets
- Implement advanced architectures including LLMs (GPT, Gemini, LLaMA), Retrieval-Augmented Generation (RAG), and Agentic Frameworks
- Build and optimize end-to-end pipelines using Python (Sci-kit Learn, Pandas, Flask, LangChain), PySpark, T-SQL and SQL
- Develop and fine-tune multiple GenAI models for NLP, summarization, prompt engineering, and conversational AI
- Apply MLOps best practices: model versioning, drift analysis, quantization, MLFlow, containerization with Docker, and CI/CD pipelines
- Work with cloud platforms: Azure (Databricks, ML Studio, Data Factory, Data Lake, Delta Tables), AWS, and GCP for scalable deployments
- Integrate data warehousing solutions like Snowflake and manage large-scale data pipelines
- Collaborate in an Agile environment, participate in sprint planning, and maintain code repositories using GitHub/Git
- Ensure compliance with security and governance standards for healthcare data
- Coach and mentor junior team members
- Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI
Requirements:
- Bachelor's degree in CS or IT related field
- 5+ years of hands-on experience in AI/ML techniques like Prompt Engineering, RAG (Retrieval Augmented Generation) and Agentic AI
- 5+ years of experience and strong expertise in Python, PySpark, T-SQL, SQL, and big data technologies (Hadoop, Spark)
- 2+ years of experience in statistics, data modeling, and simulation
- 1+ years of experience with Generative AI frameworks/architectures (LangChain, HuggingFace, OpenAI APIs)
- 1+ years of experience with any one of the cloud technologies: Azure (Databricks, ML Studio), AWS Bedrock, Azure Foundry, Kafka, GCP, and cloud-native AI services
- 1+ years of experience with CI/CD pipelines, GitHub Actions, and containerization tools
- 1+ years of experience with LLM security, prompt engineering, and responsible AI practices
- Experience with LLMs (GPT, Gemini, LLaMA) and prompt-based learning
- Knowledge of Kafka, TensorFlow, and advanced deep learning architectures (CNNs, Autoencoders)
- Strong understanding of Agile methodologies and DevOps practices
- Internal Data management and big data handling experience
- Excellent problem-solving skills and ability to handle ambiguity
- All Telecommuters will be required to adhere to UnitedHealth Group's Telecommuter Policy