Associate AI/ML Engineer

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.  

As an Associate AI/ML Engineer, you will join an innovative engineering team dedicated to transforming healthcare delivery through advanced artificial intelligence and machine learning solutions. In this role, you will contribute directly to designing, developing, and operationalizing generative AI, retrieval-augmented generation (RAG) systems, and agentic workflows that solve complex business and clinical challenges. You will collaborate with cross-functional software and data teams to build secure, scalable, and reliable production-grade AI applications using modern cloud services and enterprise data platforms.

Primary Responsibilities:

• Design and implement AI systems for conversational search in M&R Sales content
• Develop AIML based data ingestion quality gates based on pattern analysis
• Evaluate, debug, and improve conversational AI to ensure accuracy and efficiency
• Monitor and optimize system performance for latency, cost, and reliability
• Explore and apply reinforcement learning and self-improving techniques
• Collaborate and communicate effectively with cross-functional teams and stakeholders to deliver scalable solutions
• Ensure responsible and ethical AI practices throughout all stages of development
• Design, build, and deploy production-grade AI-powered solutions, including agentic workflows, RAG architectures, and conversational AI applications that solve complex enterprise challenges.
• Develop, optimize, and maintain scalable batch and real-time streaming data pipelines using Spark (including Spark Structured Streaming), Scala, and Python within Azure Databricks and Snowflake.
• Integrate event-streaming technologies (e.g., Apache Kafka, Azure Event Hubs) to process continuous, low-latency data feeds for real-time inference, dynamic context retrieval, and vector store updates
• Expose AI model outputs and streaming analytics via secure REST APIs and microservices, connecting data streams to downstream business platforms and interactive PowerBI dashboards
• Apply security best practices, data privacy standards, and responsible AI principles across all data processing and application workflows
• 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:

• 3+ years of software engineering experience, including hands-on experience building AI/GenAI or LLM-based applications (e.g., RAG systems, agentic workflows, or AI chatbots)
• Experience designing and building both batch and real-time streaming data pipelines using Spark, Scala, or Python
• Hands-on experience working with event-streaming or distributed messaging platforms (e.g., Apache Kafka, Azure Event Hubs, or Spark Structured Streaming)
• Experience building data pipelines within cloud data platforms such as Azure Databricks or Snowflake
• Practical experience integrating foundation models via commercial or open-source APIs (e.g., Azure OpenAI, OpenAI, Anthropic, Amazon Bedrock)
• Hands-on experience with at least one GenAI orchestration framework (e.g., LangChain, LangGraph, or Spring AI)
• Firm understanding of RAG components (chunking, embeddings, vector indexing, retrieval, prompt engineering) and agentic patterns (tool/function calling, memory, orchestration)
• Solid understanding of REST APIs, microservices architecture, Git, CI/CD pipelines, and Docker containerization
• Awareness of security, privacy, and responsible AI practices when building production systems

Preferred Qualifications:

• Relevant certifications in data engineering or cloud AI/ML (e.g., Databricks Certified Data Engineer, Azure AI Engineer Associate, Confluent Certified Developer for Apache Kafka)
• Experience modeling and serving streaming or batch datasets to PowerBI for operational and executive reporting
• Experience implementing LLM observability, evaluation, and guardrail frameworks (e.g., MLflow, Langfuse, or TruLens)
• Familiarity with data governance, schema registry, and data quality frameworks in streaming architectures
• Good understanding of analytics tools: Python, SQL, Databricks, Snowflake
• Good knowledge of Business intelligence tools like Tableau/Power BI, etc.
• Solid problem-solving skills
• Good knowledge around Predictive & Prescriptive Analytics techniques like Hypothesis testing, Probability, Supervised & Unsupervised Learnings
• Ability in slicing and dicing of data structures, Natural Language Processing and good to have fundamental understanding on Gen-AI & Large Language Models

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.