Remote AI Engineer for Healthcare LLM & RAG Pipelines

Eliassen Group; Salem (OR); Remote; USD 125,000 - 165,000; Full time

Job summary

Eliassen Group is seeking an AI Engineer to design, test, and deploy AI-powered healthcare solutions within the PACE program, mostly remote. The role emphasizes enterprise LLMs, RAG pipelines, and agentic workflows in production settings.

You will work with Azure cloud tools, Python, and DevOps practices, supporting POC to production lifecycles while ensuring HIPAA compliance and secure data handling.

Qualifications

• Minimum three years of hands-on AI/ML engineering experience or related field.

Responsibilities

• Design, build, and deploy AI-powered applications using enterprise LLMs to meet PACE business requirements.
• Architect and implement RAG systems grounded in proprietary data with accuracy, relevance, and compliance.
• Own the development lifecycle from ideation through production deployment.
• Research and build agentic AI workflows using LangGraph, LangChain, or Copilot Studio.
• Architect and deploy AI services in private cloud environments, primarily Azure, using secure configurations.
• Evaluate and integrate across multiple models based on performance, cost, latency, and compliance.
• Implement AIOps and MLOps practices including monitoring, versioning, automated testing, and CI/CD.
• Continuously evaluate emerging AI tools and models and recommend improvements.
• Work a varied schedule that may include evenings, nights, weekends, and overtime.

Skills

Python

Azure

Docker

LangChain

LangGraph

Copilot Studio

DevOps/CI-CD

HIPAA

Agile/Scrum

L2M?LO? not needed

Education

Bachelor’s Degree in Computer Science, AI, Computer Engineering, or related field

Tools

Azure DevOps

Docker

Job description

Eliassen Group is seeking an AI Engineer to design, test, and deploy AI-powered healthcare solutions within the PACE program, mostly remote. The role emphasizes enterprise LLMs, RAG pipelines, and agentic workflows in production settings.

You will work with Azure cloud tools, Python, and DevOps practices, supporting POC to production lifecycles while ensuring HIPAA compliance and secure data handling.