The Role
Build and operationalize production-grade generative AI, RAG, conversational AI, and agentic workflow solutions. Develop batch and real-time streaming pipelines with Spark, Scala, Python, Azure Databricks, and Snowflake. Integrate Kafka or Azure Event Hubs, foundation models, vector retrieval, REST APIs, and microservices. Optimize system performance, evaluate model quality, apply responsible AI and security practices, and collaborate with cross-functional teams.
Summary Generated by Built In
Requisition Number: 2390921
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:
Required Qualifications:
Preferred Qualifications:
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.
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.
Skills Required
- 3+ years of software engineering experience, including hands-on experience building AI, generative AI, or LLM-based applications
- Experience designing and building batch and real-time streaming data pipelines using Spark, Scala, or Python
- Hands-on experience with event-streaming or distributed messaging platforms such as 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 through commercial or open-source APIs
- Hands-on experience with at least one generative AI orchestration framework, such as LangChain, LangGraph, or Spring AI
- Understanding of RAG components, including chunking, embeddings, vector indexing, retrieval, and prompt engineering
- Understanding of agentic patterns, including tool or function calling, memory, and orchestration
- Understanding of REST APIs, microservices architecture, Git, CI/CD pipelines, and Docker containerization
- Awareness of security, privacy, and responsible AI practices for production systems
- Relevant data engineering or cloud AI/ML certifications
- Experience serving streaming or batch datasets to Power BI for reporting
- Experience with LLM observability, evaluation, and guardrail frameworks such as MLflow, Langfuse, or TruLens
- Familiarity with data governance, schema registry, and data quality frameworks in streaming architectures
- Knowledge of Python, SQL, Databricks, and Snowflake analytics tools
- Knowledge of Tableau or Power BI
- Problem-solving skills
- Knowledge of predictive and prescriptive analytics, hypothesis testing, probability, and supervised and unsupervised learning
- Ability to analyze data structures and knowledge of natural language processing and generative AI or large language models
Optum Compensation & Benefits Highlights
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Leave & Time Off Breadth — Paid time off is often regarded as generous, with meaningful accrual and flexibility to use it. While practices can vary by team, the overall time-off offering stands out as a relative strength.
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Retirement Support — A 401(k) plan with employer matching is available and generally well-regarded for supporting long-term savings. It remains valuable, though candidates should verify the current match formula.
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Parental & Family Support — Programs such as parental leave, family medical leave, and adoption assistance are included as notable elements of the total rewards package. These resources can meaningfully support work-life balance when applicable to the role and location.
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The Company
What We Do
Optum, part of the UnitedHealth Group family of businesses, 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. At Optum, we support your well-being with an understanding team, extensive benefits and rewarding opportunities. By joining us, you’ll have the resources to drive system transformation while we help you take care of your future. We recognize the power of connection to drive change, improve efficiency and make a difference in health care. Join a team where your skills and ideas can make an impact and where collaboration is key to creating technology that produces healthier outcomes.
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Optum Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Optum has three workplace models that balance the needs of the business and the responsibilities of each role. These models, core on‑site (5 days/week), hybrid (4 days/week) and telecommute or fully remote, vary by country, role and location.
Typical time on-site:
Not Specified
