AI Engineer - Remote

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.

We are seeking a highly skilled and motivated Senior AI Engineer with deep expertise in Generative AI, Large Language Models (LLMs), and cloud-native AI platforms. The ideal candidate will have a strong foundation in AI/ML, hands-on experience with LangChain, LangGraph, and familiarity with AWS Bedrock and Azure AI Foundry. This role involves building secure, scalable, and responsible GenAI solutions while collaborating across teams to drive innovation and impact.

You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges.

For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.

Primary Responsibilities

• Design, develop, and deploy AI/ML and Generative AI models for predictive, prescriptive, and generative analytics across healthcare datasets
• Implement advanced architectures including LLMs (GPT, Gemini, LLaMA), Retrieval-Augmented Generation (RAG), and Agentic Frameworks
• Build and optimize end-to-end pipelines using Python (Sci-kit Learn, Pandas, Flask, LangChain), PySpark, T-SQL and SQL
• Develop and fine-tune multiple GenAI models for NLP, summarization, prompt engineering, and conversational AI
• Apply MLOps best practices: model versioning, drift analysis, quantization, MLFlow, containerization with Docker, and CI/CD pipelines
• Work with cloud platforms: Azure (Databricks, ML Studio, Data Factory, Data Lake, Delta Tables), AWS, and GCP for scalable deployments
• Integrate data warehousing solutions like Snowflake and manage large-scale data pipelines
• Collaborate in an Agile environment, participate in sprint planning, and maintain code repositories using GitHub/Git
• Ensure compliance with security and governance standards for healthcare data
• Coach and mentor junior team members

Technical Skillset

• AI/ML Foundations

• Design and implement machine learning and deep learning models for classification, NLP tasks.
• Build and maintain end-to-end ML pipelines including data preprocessing, model training, evaluation, and deployment.

• Generative AI & LLM Engineering

• Develop and fine-tune LLM-based applications using LangChain, LangGraph, and other GenAI frameworks.
• Build Multi Agentic workflows and RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases.
• Leverage AWS Bedrock and Google Vertex AI for scalable and production-grade GenAI deployments.

• LLM Security & Responsible AI

• Implement guardrails to prevent prompt injection, reduce hallucinations, and ensure safe model outputs.
• Apply best practices for LLM security, including output moderation, access control, and auditability.
• Ensure compliance with Responsible AI principles-fairness, transparency, and explainability.

• Cloud-Native AI Development

• Deploy and manage GenAI solutions on AWS and Google Suite, utilizing services like Bedrock, SageMaker, Vertex AI.
• Integrate LLMs with enterprise systems using REST APIs, SDKs, and orchestration tools.

• Collaboration & Mentorship

• Work closely with product managers, data scientists, and platform teams to translate business needs into GenAI solutions.
• Mentor junior engineers and contribute to internal knowledge-sharing initiatives.

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications

• 5 years of hands-on experience in AI/ML techniques like Prompt Engineering , RAG (Retrieval Augmented Generation) and Agentic AI
• Hands-on experience with Generative AI frameworks/arc