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:- Builds AI solutions that solve real-world healthcare challenges, providing the opportunity to take AI use cases from rapid prototyping to production while developing participant context engines, RAG pipelines, and intelligent applications that can directly support the teams caring for our most vulnerable seniors
- Works at the intersection of applied AI, healthcare, and secure cloud technology, with the opportunity to experiment with emerging LLMs, agentic frameworks, and multi-model architectures while solving the unique privacy, security, and compliance challenges of working with sensitive healthcare data
We care about our team members. 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 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 in computer science, AI, computer engineering, or other relevant field; 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
- Demonstrated experience designing and deploying RAG pipelines, including vector databases, embedding strategies, chunking optimization, and retrieval evaluation
- 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
- Advanced proficiency in Python for AI application development, API integration, and data pipeline construction
- Hands-on experience with Azure AI services (AI Foundry, Managed Identities, Key Vault, private networking) and Docker-based deployments in secure cloud environments
- Proficiency with Azure DevOps (or equivalent) for building CI/CD pipelines that automate testing and deployment of AI applications
- Solid understanding of agentic architectures and frameworks such as LangChain, LangGraph, Semantic Kernel, or Copilot Studio
- Experience working in Agile/Scrum environments with iterative development cycles and rapid POC delivery
- Familiarity with HIPAA, PHI handling, and the compliance requirements unique to healthcare technology is preferred
- Understanding of the PACE model of care and how technology can improve participant outcomes and operational workflows preferred
- Experience benchmarking and comparing LLM providers across dimensions such as accuracy, cost, latency, and safety preferred
- Secondary cloud experience with AWS AI/ML services is a plus
We're seeking an AI engineer who is energized by turning emerging AI capabilities into production-ready solutions, building intelligent applications with LLMs and agentic workflows, and using AI to solve meaningful healthcare challenges. If you're ready to join a team that values both its participants and team members, we'd love to hear from you!
Compensation consists of base salary plus bonus. WelbeHealth offers a competitive total rewards package that includes a 401(k) match, comprehensive healthcare coverage, and a broad range of additional benefits. Actual compensation will be determined based on experience and relevant qualifications.
Compensation Offering
$90,281.44-$119,171.49 USD
