At WelbeHealth, we serve our communities’ most vulnerable seniors through shared intention, pioneering spirit, and the courage to love. These core values and our participant-focus lead the way no matter what.

The AI Engineer is accountable for building, testing, and deploying AI-powered solutions that address real-world healthcare challenges within our PACE (Program of All-Inclusive Care for the Elderly) program. This role will leverage enterprise AI models - not build or finetune them - to create intelligent applications such as participant context engines, retrieval-augmented generation (RAG) pipelines, and agentic workflows. The AI Engineer will stay current with the rapidly evolving AI landscape and translate emerging capabilities into production-ready solutions for our business.

This role is different because the AI Engineer at WelbeHealth:

• Designs and delivers AI-powered solutions that transform how care teams access information, automate complex workflows, and support better participant outcomes through RAG, agentic AI, and enterprise large language models
• Works at the forefront of applied AI innovation, evaluating emerging technologies and translating them into secure, scalable, production-ready applications that enhance operational efficiency, improve decision-making, and support the evolving needs of the PACE model

That’s why we offer:

• Medical insurance coverage (Medical, Dental, Vision)
• Work/life balance - We mean it! 17 days of personal time off (PTO), 12 holidays observed annually, and 6 sick days
• 401K savings + match
• Comprehensive compensation package including base pay and bonus
• And additional benefits!

On the day-to-day, you will:

• Design, build, and deploy AI-powered applications using enterprise LLMs (OpenAI, Anthropic Claude, Google Gemini), as well as translate PACE business requirements, such as building rich participant context, into production-ready AI solutions
• Architect and implement RAG systems that ground AI responses in WelbeHealth's proprietary data, ensuring accuracy, relevance, and compliance with healthcare data standards
• Own the full development lifecycle for new AI use cases from ideation and rapid POC development through validation, iteration, and production deployment
• Research and build agentic AI workflows (using frameworks such as LangGraph, LangChain, or Copilot Studio) that evolve our systems toward autonomous, goal-oriented agents capable of handling complex multi-step healthcare processes
• Architect and deploy AI services within private cloud environments (primarily Azure; AWS as needed), utilizing Docker containers, private endpoints, managed identities, and secure VNET configurations
• Evaluate and integrate across the frontier model landscape, selecting the right model for each use case based on performance, cost, latency, and compliance requirements
• Implement AIOps and MLOps best practices, monitoring, versioning, automated testing, and CI/CD pipelines, to ensure all AI applications are reliable, scalable, and maintainable
• Continuously evaluate emerging AI tools, techniques, and model releases, as well as proactively recommend new approaches that can improve participant outcomes, operational efficiency, or developer productivity

Job requirements include:

• Bachelor’s degree required in computer science, AI, computer engineering, or other relevant fields; master’s degree preferred
• Minimum of three (3) years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with a strong AI focus
• RAG and Retrieval Systems: Demonstrated experience designing and deploying retrieval-augmented generation pipelines, including vector databases, embedding strategies, chunking optimization, and retrieval evaluation
• Enterprise LLM Integration: Proven ability to build applications on top of commercial LLM APIs (OpenAI, Anthropic, Google) including prompt engineering, structured output handling, function/tool calling, and context window management
• Python: Advanced proficiency in Python for AI application development, API integration, and data pipeline construction
• Cloud & Containerization: Hands-on experience with Azure AI services (AI Foundry, Managed Identities, Key Vault, private networking) and Docker-based deployments in secure cloud environments
• DevOps & CI/CD: Proficiency with Azure DevOps (or equivalent) for building CI/CD pipelines that automate testing and deployment of AI applications

We are seeking an AI Engineer who is curious, innovative, and hands-on, with a passion for applying artificial intelligence to solve real-world healthcare challenges. The ideal candidate combines strong technical expertise with a builder’s mindset and is excited to develop scalable AI solutions that improve the experience of our participants, care teams, and operational partners. If you’re ready to join a team that values both its participants and team members, we’d love to hear from you!