Overview
Remote
Depends on Experience
Contract - Independent
Contract - W2
Skills
AI
Azure AI
AI/ML
Azure ML
healthcare
life sciences
Job Details
Role: AI Engineers
Location: Remote role
Position: W2 or 1099
We re a leading healthcare organization committed to delivering exceptional patient outcomes and operational excellence through cutting-edge AI/ML solutions. As part of our AI/ML engineering team, you ll help architect, build, and deploy enterprise-grade intelligent applications on Microsoft Azure that drive efficiency, compliance, and superior patient experiences.
Position Summary
As an AI Engineer on our team, you will design, develop, and productionize AI-powered services spanning document intelligence, semantic search, conversational agents, and retrieval-augmented generation (RAG) pipelines. You ll also implement agentic frameworks with Model Context Protocol (MCP) for orchestrating multi-step workflows, integrating seamlessly via APIs. You ll partner closely with data scientists, product owners, and DevOps to translate clinical and operational use cases into robust, scalable solutions that comply with healthcare regulations (e.g., HIPAA).
Key Responsibilities
Agentic Frameworks & Orchestration:
o Design and implement agentic architectures that coordinate multiple AI agents (SLMs/LLMs) via MCP to decompose goals, manage state, and execute complex tasks autonomously.
o Define MCP schemas and handlers for context propagation between agents and external services.
Architecture & Design:
Define end-to-end AI solution architectures leveraging Azure AI Services (Document Intelligence, Azure Cognitive Search, Azure OpenAI, Bot Framework).
o Design RAG pipelines that securely retrieve and fuse internal medical knowledge with LLM inference.
API Integration & Microservices:
o Build and maintain RESTful and gRPC APIs to expose AI capabilities to downstream applications (EHR, member portals).
o Integrate third-party clinical and operational APIs (e.g., FHIR endpoints, appointment-scheduling services) with AI pipelines.
Development & Integration:
o Implement production-grade Python code for data ingestion, model orchestration, and API endpoints.
o Develop, tune, and maintain prompt engineering frameworks to optimize OpenAI/LLM performance on clinical content.
o Integrate Azure Document Intelligence Center for OCR, key-value extraction, and form processing.
o Build conversational experiences using Azure Bot Service/Health Bot and custom LLM backends.
Deployment & Operations:
o Containerize AI microservices (Docker, Kubernetes) and deploy via Azure Kubernetes Service or Azure App Services.
o Implement CI/CD pipelines (GitHub Actions, Azure DevOps) for model retraining, testing, and promotion across environments.
o Monitor model performance, data drift, and system health; implement logging, alerting, and observability (Application Insights).
Governance & Compliance:
o Collaborate with Security and AI Governance teams to enforce Responsible AI practices, data privacy, and HIPAA controls.
o Document solution designs, runbooks, and technical specifications.
Required Qualifications
MS or PhD in Computer Science, AI/ML, Mechatronics, Electrical Engineering, or related field
3+ years hands-on experience building AI/ML solutions in production environments
Expert proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch)
Deep experience with Microsoft Azure AI Services:
o Azure AI Document Intelligence (Form Recognizer, Custom Vision)
o Azure Cognitive Search
o Azure OpenAI Service
o Azure Bot Framework / Health Bot
Demonstrable work with RAG architectures, vector embeddings, and semantic retrieval
Strong prompt engineering skills for optimizing LLM-based workflows
Experience designing and implementing agentic frameworks and MCP for multi-agent orchestration
Proven ability to design and integrate RESTful/gRPC APIs with AI services
Solid understanding of RESTful APIs, microservices, and container orchestration (Docker, Kubernetes)
Familiarity with DevOps: CI/CD, Infrastructure as Code (ARM templates, Bicep, Terraform)
Excellent communication skills and ability to translate complex technical concepts for cross-functional stakeholders
Preferred Qualifications
Prior experience in healthcare or life sciences, with knowledge of clinical workflows and data standards (FHIR, HL7)
Hands-on with versioned model registries (MLflow, Azure ML) and feature stores
Background in chatbot analytics, user feedback loops, and A/B testing conversational experiences
OpenAI fine-tuning experience (GPT-3.x, GPT-4) and working knowledge of privacy-preserving techniques (differential privacy, encryption)
Contributions to open-source AI projects or publications in AI/ML conferences
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.