Lead AI/ML Engineer

Requisition Number: 2392706

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.

The Principal AI/ML & Data Engineer will design, build, and operationalize enterprise-scale artificial intelligence, machine learning, generative AI, and data engineering capabilities for RxMax modernization. This role combines strong PBM domain understanding with hands-on engineering expertise to create trusted data products, intelligent applications, and reusable delivery patterns across pharmacy claims, rebates, pricing, disbursement, and operational workflows.

The engineer will help establish a sustainable internal capability by converting complex business rules and legacy knowledge into secure, scalable, well-governed solutions that improve delivery speed, quality, traceability, and maintainability.

Primary

Responsibilities

• AI/ML and Generative AI Engineering
• Design, develop, evaluate, and deploy production-grade machine learning and generative AI solutions for PBM and RxMax use cases
• Build retrieval-augmented generation solutions, enterprise search experiences, AI agents, and repository-aware engineering assistants using approved models and platforms
• Create model and prompt evaluation frameworks covering accuracy, groundedness, safety, performance, reliability, and business value
• Operationalize models and AI services through repeatable MLOps practices, monitoring, versioning, testing, and controlled release processes
• Partner with product, engineering, operations, security, and compliance stakeholders to identify high-value use cases and translate them into measurable solutions
• Data Engineering and Platform Development
• Architect and implement scalable ingestion, transformation, orchestration, and serving pipelines across PBM data domains
• Build curated data products and reusable data services using Azure, Databricks, ADLS, Spark/PySpark, SQL, Delta Lake, and related technologies
• Engineer data pipelines that support batch, near-real-time, analytical, operational, and AI workloads while meeting performance and reliability requirements
• Implement data quality controls, reconciliation, metadata, lineage, observability, retention, and recoverability throughout the data lifecycle
• Optimize data layout, partitioning, query patterns, compute usage, and storage to improve performance and cost efficiency at large scale
• Develop secure access patterns for sensitive healthcare and PBM information, including appropriate masking, least-privilege access, and auditability
• Modernization and Engineering Excellence
• Apply AI-assisted, repository-aware, and specification-driven engineering practices to accelerate modernization while preserving embedded RxMax business rules
• Create reusable frameworks for documentation, code analysis, data mapping, test generation, knowledge capture, and technical onboarding
• Build automated CI/CD pipelines with unit, integration, data-quality, security, and regression controls embedded early in the delivery lifecycle
• Collaborate with software engineering, quality engineering, SRE, DevSecOps, architecture, and data teams to deliver integrated end-to-end solutions
• Contribute to architecture decisions and proofs of concept by defining success criteria, implementing representative workloads, documenting evidence, and communicating tradeoffs
• Mentor engineers and establish practical standards, reference implementations, and reusable patterns for AI and data engineering
• 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

• Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent practical experience
• 8+ years of experience in software engineering, data engineering, machine learning engineering, or a related discipline
• 5+ years of experience designing and delivering large-scale cloud data platforms or production data products
• Demonstrated experience building and operating production AI/ML solutions, not limited to experimentation or prototypes
• Hands-on experience with Databricks, Azure Data Lake Storage, Delta Lake, Unity Catalog, orchestration, and cloud-native data services
• Experience with ML lifecycle tools and practices such as MLflow, feature engineering, model deployment, evaluation, monitoring, and retraining
• Experience designing APIs, reusable libraries, and integration patterns for data and AI-enabled applications
• Experience implementing automated testing, CI/CD, source control, infrastructure automation, and DevSecOps controls
• Advanced proficiency in Python, SQL, Spark/PySpark, distributed data processing, and software engineering practices
• Proven solid analytical, troubleshooting, communication, and technical leadership skills

Preferred

Qualifications

• Experience in pharmacy benefit management, healthcare, pharmacy claims, rebates, formularies, drug pricing, payment allocation, billing, or disbursement processing
• Experience modernizing legacy applications, data platforms, or high-volume operational systems while preserving complex business logic
• Hands-on experience with Azure AI services, Azure OpenAI or another enterprise LLM platform, embeddings, vector search, and RAG architectures
• Experience with Kafka or event streaming, change data capture, data federation, relation