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 maintain scalable data pipelines using Databricks (Spark / PySpark)
- Orchestrate and monitor workflows using Apache Airflow for batch, streaming, and incremental processing
- Build and optimize ELT pipelines in Snowflake, ensuring performance, reliability, and cost efficiency
- Develop production-quality Python code for data processing, transformations, integrations, and AI/ML workloads
- Design, build, and host APIs, AI services, and data products using modern Python frameworks
- Deploy and manage APIs, ML models, and AI services using Azure-native services (Azure Functions, App Services, API Management, Azure AI Services)
- Design and implement AI/ML and Generative AI solutions, including model integration, prompt engineering, RAG (Retrieval-Augmented Generation), and intelligent workflow automation
- Build and manage vector databases, embeddings pipelines, semantic search capabilities, and knowledge retrieval frameworks
- Develop and operationalize ML pipelines, feature engineering workflows, model monitoring, and MLOps practices
- Leverage LLMs and Agentic AI frameworks to automate data onboarding, data quality validation, metadata management, and business processes
- Apply Azure cloud best practices for security, scalability, monitoring, resiliency, governance, and cost optimization
- Implement data quality checks, lineage tracking, observability, model evaluation, and AI governance controls
- Collaborate with Data Science, Analytics, Product, and Platform teams to build AI-powered products and intelligent data solutions
- Participate in architecture design, code reviews, AI solution design, and technical decision-making
- Troubleshoot and resolve complex production issues across data platforms, AI services, ML models, and cloud infrastructure
- Evaluate emerging AI/ML technologies and drive adoption of best practices across the engineering organization
- 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
- Graduate degree or equivalent experience
- Solid hands-on experience with Databricks (Spark / PySpark) in production environments
- Experience building and hosting REST APIs, AI services, and microservices using Python frameworks
- Experience with Azure AI Services, Azure OpenAI, Azure Machine Learning, or equivalent AI platforms
- Experience working with Large Language Models (LLMs), Generative AI, RAG architectures, vector databases, embeddings, and prompt engineering
- Experience implementing AI governance, model evaluation, privacy, security, and responsible AI practices
- Experience with CI/CD pipelines, Git-based version control, Infrastructure as Code, and deployment automation
- Solid working experience with Snowflake, including data modeling, optimization, and performance tuning
- Solid experience with Microsoft Azure, including cloud-native architecture and best practices
- Knowledge of Agentic AI frameworks (e.g., Semantic Kernel, LangChain, AutoGen, CrewAI, or similar) and intelligent workflow orchestration
- Solid understanding of Machine Learning lifecycle, MLOps, model deployment, monitoring, and governance
- Solid understanding of data warehousing, ELT patterns, modern cloud data architecture, and AI-driven data products
- Proven expertise with Apache Airflow for workflow orchestration and dependency management
- Advanced Python programming skills for data engineering, API development, and AI/ML applications
- Demonstrated ability to independently own, design, and deliver end-to-end data engineering and AI/ML solutions
- Demonstrated solid problem-solving, communication, and stakeholder collaboration skills
Preferred Qualifications
- Experience developing enterprise GenAI applications in healthcare, insurance, or regulated industries
- Experience with Data Science workflows, feature stores, model serving, and ML experimentation platforms
- Experience integrating AI capabilities into business applications and enterprise data platforms
- Familiarity with Agentic AI, autonomous workflow orchestration, and intelligent document processing solutions
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.