AI Engineer

WelbeHealth

AI Engineer developing AI-powered applications leveraging enterprise AI models for healthcare applications. Creating intelligent solutions to enhance workflows and participant outcomes in the PACE program.

Posted 6/23/2026full-timeLos Angeles • California • 🇺🇸 United StatesMid-LevelSenior💰 $120,164 - $158,617 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerPythonVault

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

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!

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI application developmentAI/ML engineeringRAG systemsRetrieval-augmented generationPythonAPI integrationCloud computingContainerizationDevOpsCI/CD