Senior AI ML Engineer

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

• Analyze business requirements & functional specifications
• Adherence to the defined delivery process/guidelines
• Drive project quality process compliance
• Contribute to drive & enforce AI Engineer industry standards and best practices in the team
• 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
  
  

• Bachelor's or master's degree in computer science, Engineering, Data Science, AI/ML, or a related field
• 10+ years of experience in Data Engineering, Cloud Platform Engineering, and Enterprise Solution Architecture
• 5+ years of hands-on experience in Azure Databricks, Spark performance optimization, distributed computing, and designing scalable data platform architectures
• 3+ years of experience architecting and implementing Generative AI solutions leveraging LLMs, RAG frameworks, LangGraph, AI Agents, and enterprise AI platforms
• Proven experience designing end-to-end cloud-native architectures on Azure, including data, analytics, AI, security, and governance frameworks
• Experience leading architecture reviews, driving technical decision-making, and guiding engineering teams on scalability, reliability, security, and operational excellence
• Solid healthcare domain knowledge
• Proven solid expertise in defining enterprise data strategies, solution blueprints, architecture standards, and technology roadmaps
• Demonstrated success in driving enterprise AI adoption, establishing best practices, and delivering AI-powered business solutions at scale
• Proven solid stakeholder management and communication skills, with the ability to influence leadership, align technology strategies with business objectives, and mentor senior engineering teams
• Proven ability to determine the impact of changes in current functionality of the system
• Proven ability to handle Gen AI, RAG, LLM based assignments independently, end-to-end SDLC
• Proven ability to manage a team of AI Engineer, and provide techno-functional mentoring
• Proven flexible to collaborate with onshore business, during US business hours
• Proven flexible to support project releases, during US business hours