Healthcare AI Engineer – Generative AI & RAG

Healthcare AI Engineer – Generative AI & RAG
Location: Remote
Employment Type: Contract

Job Summary

We are looking for an AI Engineer to design, develop, and deploy AI-powered applications for real-world healthcare use cases. The role focuses on building applications using enterprise LLMs, rather than developing or fine-tuning foundation models.

The ideal candidate will have strong hands-on experience with RAG, LLM integration, agentic AI, Python, Azure AI services, cloud deployment, and CI/CD. You will take AI solutions from rapid prototyping through production deployment while ensuring security, scalability, reliability, and compliance.

Key Responsibilities

Design and develop AI applications using enterprise LLMs such as OpenAI, Anthropic Claude, and Google Gemini.
Build and deploy RAG pipelines using vector databases, embeddings, chunking, retrieval, and evaluation techniques.
Develop AI prototypes and take them through POC, validation, iteration, and production deployment.
Build agentic AI workflows using frameworks such as LangGraph, LangChain, Semantic Kernel, or Microsoft Copilot Studio.
Integrate LLM capabilities including prompt engineering, structured outputs, function/tool calling, and context management.
Deploy AI services in secure Azure cloud environments using Docker, managed identities, Key Vault, private endpoints, and VNETs.
Evaluate and orchestrate multiple LLM providers based on accuracy, cost, latency, performance, and security.
Implement MLOps/AIOps, monitoring, automated testing, versioning, and CI/CD for AI applications.
Build scalable APIs and data pipelines using Python.
Research emerging AI technologies and identify opportunities to improve business processes and AI capabilities.
Work closely with product, engineering, and business stakeholders in an Agile/Scrum environment.
Ensure AI solutions follow applicable healthcare data privacy, security, and compliance requirements, including HIPAA and PHI handling.
Required Skills & Experience

Bachelor’s degree in Computer Science, Artificial Intelligence, Computer Engineering, or a related field.
3+ years of hands-on experience in AI/ML engineering, applied AI, or software engineering with a strong AI focus.
Strong hands-on experience building RAG applications and retrieval systems.
Advanced Python programming skills.
Experience integrating commercial LLM APIs such as OpenAI, Anthropic, or Google Gemini.
Strong understanding of prompt engineering, embeddings, vector databases, context management, and retrieval evaluation.
Experience with agentic AI frameworks such as LangGraph, LangChain, Semantic Kernel, or Copilot Studio.
Hands-on experience with Azure AI services / Azure AI Foundry.
Experience with Docker and secure cloud deployments.
Experience with Azure DevOps or equivalent CI/CD tools.
Understanding of LLM evaluation and model selection based on accuracy, cost, latency, and safety.
Experience working in Agile/Scrum development environments.
Preferred Qualifications

Experience working with HIPAA, PHI, and healthcare technology.
Knowledge of PACE or healthcare care-management workflows.
Experience with AWS AI/ML services.
Master’s degree in a relevant technical field.
Experience benchmarking multiple LLM providers and implementing multi-model orchestration.
Key Technologies

Python | RAG | LLMs | OpenAI | Anthropic Claude | Google Gemini | Azure AI Foundry | LangGraph | LangChain | Semantic Kernel | Copilot Studio | Vector Databases | Embeddings | Docker | Azure DevOps | CI/CD | AWS