AI Specialist

6-8 month assignment for experienced AI Engineer with possibility of extension

Full time Monday through Friday must work 8 am to 5 pm Pacific Standard Time. Must be based in United States.

Job Summary:
The AI Engineer is responsible 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. The AI Engineer will leverage enterprise AI models to not build or fine-tune 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. The AI Engineer collaborates effectively with colleagues and stakeholders to promote WelbeHealth values, team culture, and mission.

Job Responsibilities:

• Enterprise AI Application Development: Design, build, and deploy AI-powered applications using enterprise LLMs (OpenAI, Anthropic Claude, Google Gemini).
• Translate PACE business requirements such as building rich participant context into production-ready AI solutions.
• RAG Pipeline Engineering: Architect and implement retrieval-augmented generation (RAG) systems that ground AI responses in WelbeHealth's proprietary data, ensuring accuracy, relevance, and compliance with healthcare data standards.
• Hands-On Prototyping & Delivery: Own the full development lifecycle for new AI use cases from ideation and rapid POC development through validation, iteration, and production deployment.
• Agentic Framework Development: 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.
• Secure Cloud Deployment: 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.
• Multi-Model Orchestration: Evaluate and integrate across the frontier model landscape, selecting the right model for each use case based on performance, cost, latency, and compliance requirements.
• Operational Excellence: Implement AIOps and MLOps best practices monitoring, versioning, automated testing, and CI/CD pipelines to ensure all AI applications are reliable, scalable, and maintainable.
• Technology Scouting: Continuously evaluate emerging AI tools, techniques, and model releases.
• Proactively recommend new approaches that can improve participant outcomes,

operational efficiency, or developer productivity.

• Must be willing and have the ability to work a varied schedule that may include evening nights, weekends and overtime.
• Complete all required documentation in a timely and accurate manner.
• Protect privacy and maintain confidentiality of all company procedures and information about team members, participants, and families.
• Follow WelbeHealth policies and procedures and participate in any required Quality Improvement activities, staff training and meetings.
• Communicate regularly with Supervisor and team regarding workload and priorities.
• Timely completion of all mandated trainings and education.
• Timely completion of all mandated occupational health screenings as needed.
• Exercises flexibility in performing assignments as business needs evolve.
• Other duties as assigned.

Skills:

Required Skills & Experience:

• Minimum of three (3) years of hands-on experience in AI/ML engineering, applied AI development, or software engineering with a strong AI focus.
• Experience and competency working with people from diverse backgrounds and cultures.
• RAG & 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.
• Agentic AI Patterns: Solid understanding of agentic architectures and frameworks such as LangChain, LangGraph, Semantic Kernel, or Copilot Studio.
• Agile Delivery: Experience working in Agile/Scrum environments with iterative development cycles and rapid POC delivery.
• Excellent organizational and communication skills.
• Ability to work independently with minimal supervision.
• Demonstrated ability to prioritize in a fast-paced environment.
• Commitment to unlocking the full potential of our most vulnerable seniors.

Preferred Skills & Experience:

• Healthcare Domain: Familiarity with HIPAA, PHI handling, and the compliance requirements unique to healthcare technology.
• PACE Program Knowledge: Understanding of the PACE model of care and how technology can improve participant outcomes and operational workflows.
• Model Evaluation: Experience benchmarking and comparing LLM providers across dimensions such as accuracy, cost, latency, and safety.
• AWS: Secondary cloud experience with AWS AI/ML services.

Education:

Required Education:

• Bachelor’s Degree required in Computer Science, AI, or Computer Engineering.

Preferred Education:

• Master’s Degree in the above.

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