Join Optum, a global leader dedicated to improving health outcomes through innovative technology. This role at OptumRx focuses on driving advancements in pharmacy and healthcare operations by developing and deploying cutting-edge AI, Machine Learning, and Generative AI solutions. You will harness extensive healthcare and enterprise data to create predictive models and intelligent applications, including LLM-powered tools, to achieve significant business and patient benefits. This fast-paced, data-centric environment requires a blend of deep technical expertise and strong business insight to tackle complex healthcare challenges.

Optum is committed to fostering a culture of inclusion and providing comprehensive benefits and career development. We aim to advance health optimization worldwide and invite you to be part of our mission to Care, Connect, and Grow together.

Lead the design, development, and deployment of Generative AI applications, including conversational AI, summarization, and medical document intelligence using LLMs. Implement and optimize Retrieval-Augmented Generation (RAG) pipelines and apply advanced prompt engineering and fine-tuning techniques. Develop AI solutions leveraging healthcare data, ensuring accuracy, explainability, and compliance.

Build and productionize machine learning models, perform extensive feature engineering on large-scale datasets, and create predictive/prescriptive analytics for healthcare outcomes. Establish processes for model evaluation, monitoring, and continuous retraining.

Develop scalable AI services, integrate third-party AI APIs and open-source models, and build agentic AI workflows. Work with vector databases for low-latency performance and construct data pipelines for massive healthcare transactions.

Collaborate with stakeholders to translate business needs into AI/ML solutions, applying knowledge of healthcare standards (FHIR, HL7) and data privacy. Implement Responsible AI practices and participate in technical discussions and mentoring.

A Bachelor's or Master's degree in Computer Science, AI, Data Science, or Robotics, or an MCA, is required, coupled with over 7 years of professional experience in Data Science and Machine Learning, including at least 4 years of hands-on production AI/ML solution deployment. Multiple certifications in Cloud, AI, ML, or Data Engineering are preferred.

Demonstrated expertise in building scalable data pipelines, feature engineering, and proficiency in Python, PySpark, and SQL. Proven experience with LLMs (GPT, Llama, Claude, Mistral) and frameworks like LangChain and LlamaIndex is essential.

Strong understanding of machine learning foundations, including supervised and unsupervised learning, deep learning, NLP, and statistical modeling, particularly applied to healthcare data. Familiarity with healthcare data models and interoperability standards (FHIR, HL7, ICD, CPT, SNOMED) is crucial.

Experience with major cloud AI platforms (Azure AI, AWS SageMaker, Google Vertex AI) and excellent communication skills to articulate complex technical concepts are required. At least 3 years of experience in a healthcare-related domain is necessary.