AI/ML Engineer – Generative AI & Claims Automation

About the role

Optum, part of UnitedHealth Group, is hiring an AI/ML Engineer in Hyderabad to design and deliver AI and Generative AI solutions for Core Claims initiatives such as duplicate overpayments, fraud, waste and abuse disputes, and first-pass claims. The role also covers large language models, prompt engineering and retrieval-augmented generation.

Key responsibilities

• Design, develop and implement AI/ML and Generative AI solutions for Core Claims, including duplicate overpayments, FWA disputes and first-pass claims.
• Build and deploy LLM-powered applications, prompt engineering solutions and RAG frameworks.
• Use AI to automate claims workflows such as classification, intelligent routing, document understanding, decision support and operational triage.
• Work with engineering, product, analytics and business teams to build scalable AI solutions.
• Set up model evaluation, performance testing, validation and continuous improvement frameworks.
• Partner with data science and engineering teams on feature engineering, model deployment, inference optimization and production support.
• Follow responsible AI practices, including explainability, governance, fairness and model validation.
• Keep up with advances in AI, Generative AI and LLMs.

Required profile

• Bachelor's or Master's degree in Computer Science, AI, Machine Learning, Data Science or a related field.
• 7+ years of experience in AI/ML solution development, with hands-on Generative AI and LLM experience.
• Experience building and deploying LLM apps, RAG architectures, prompt engineering and intelligent automation.
• Experience with model evaluation, performance optimization and AI validation.
• Experience working with cross-functional teams; knowledge of Responsible AI principles.
• Preferred: healthcare, claims, payment integrity, fraud detection or operational analytics background, and knowledge of Medicare & Retirement claims.

Required skills

• Solid proficiency in Python and modern AI/ML frameworks and toolchains.
• Preferred: cloud-based AI/ML platforms and MLOps practices.