Job Title: AI Engineer
Job Location: Covina, CA
Job Duration: 7 Months (possibility of extension)
Payrate: $70.00/ hr. on w2

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 client 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 client'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 client 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.

Required Education:

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

Preferred Education:

• Master’s Degree in the above.

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.