Sr AI/ML Data Engineer Remote or Office-Based in MN/DC

Optum is seeking a Senior AI/ML engineer to build AI-powered data products and digital experiences for its analytics and healthcare platforms. The role develops full-stack applications, AI/ML capabilities, and cloud-native data solutions for self-service analytics, operational insights, and quality improvement.

Responsibilities:

• Design, develop, and deploy AI/ML and Generative AI solutions using LLMs, RAG, agents, and modern AI frameworks
• Build scalable full-stack applications using React, TypeScript, JavaScript, Java/Spring Boot, Python, REST APIs, and SQL
• Develop intuitive user experiences, dashboards, reporting solutions, and AI-enabled workflows
• Build and enhance self-service analytics, reporting, and data exploration capabilities
• Develop applications supporting quality, patient safety, benchmarking, insights, action management, and workflow automation
• Integrate applications with enterprise data platforms and cloud-native data ecosystems
• Design and implement microservices, APIs, data models, and event-driven architectures
• Apply engineering best practices including CI/CD, automated testing, observability, security, and performance optimization
• Collaborate with product, analytics, business, and platform teams to deliver high-quality solutions
• Provide technical leadership, mentor engineers, and contribute to architecture and technology decisions

Requirements:

• Bachelor's degree or equivalent practical experience
• 5+ years of experience building production-grade data platforms and pipelines using Python or Java, SQL, Spark/PySpark, and Databricks or equivalent technologies
• 3+ years of experience designing batch, streaming, and event-driven data solutions using cloud platforms such as AWS, Azure, or GCP
• 2+ years of experience delivering production Generative AI solutions, including RAG, retrieval, evaluation, monitoring, and AI/ML deployment enablement
• 2+ years of experience with modern data engineering practices, including data quality and observability, metadata, lineage, and governance
• Demonstrated ability to lead technical initiatives, mentor engineers, influence cross-functional teams, and translate ambiguous requirements into scalable solutions
• Experience with Databricks, Snowflake, Microsoft Fabric, Delta Lake, or similar cloud data platforms
• Experience with Generative AI architectures, including RAG, vector search, and model evaluation frameworks
• Experience with streaming technologies such as Kafka, Event Hubs, or Kinesis
• Experience with MLOps capabilities including feature stores, model registries, and deployment automation
• Experience with data quality and observability platforms
• Familiarity with metadata-driven architectures, knowledge graphs, or entity resolution concepts
• Experience in healthcare data, analytics, and PII/PHI-compliant solutions