Agentic AI Engineer

Role: Agentic AI Engineer
Interview: 2 rounds of interview (Virtual)
Onsite: Dallas, TX. (Can be Remote for suitable candidate)
Rate: $55/hr on C2C

Job Overview

We are seeking a highly skilled Agentic AI Engineer to join our healthcare client’s team. This is a fully remote opportunity to work on cutting-edge AI solutions, focusing on building intelligent, autonomous agents that enhance healthcare workflows and decision-making.

The ideal candidate will have strong expertise in Python, LangGraph, FastAPI, and Large Language Models (LLMs), along with hands-on experience in designing and implementing end-to-end agentic AI systems.

Key Responsibilities

• Design, develop, and deploy agentic AI solutions tailored for healthcare use cases
• Build and orchestrate AI agents using LangGraph or similar frameworks
• Develop scalable backend services and APIs using Python and FastAPI
• Integrate and optimize LLMs (OpenAI, open-source models, etc.) into applications
• Implement multi-agent workflows, tool usage, and reasoning pipelines
• Ensure security, compliance, and data privacy in healthcare environments (HIPAA awareness preferred)
• Collaborate with cross-functional teams, including data engineers, clinicians, and product teams
• Monitor, evaluate, and improve agent performance and reliability

Required Skills & Experience

• 5+ years of experience in software development with strong Python expertise
• Hands-on experience with LangGraph or similar agent orchestration frameworks
• Strong experience building APIs using FastAPI or similar frameworks
• Solid understanding of LLMs, prompt engineering, and agent architectures
• Experience with end-to-end agent building lifecycle (planning, memory, tools, orchestration, evaluation)
• Knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG)
• Familiarity with cloud platforms (AWS, Google Cloud Platform, or Azure)
• Strong problem-solving and system design skills

Preferred Qualifications

• Experience in the healthcare domain or regulated environments
• Knowledge of HIPAA compliance and secure data handling
• Experience with multi-agent systems and autonomous workflows
• Familiarity with frameworks like LangChain, AutoGen, or CrewAI
• Exposure to MLOps / LLMOps practices