Lead AI Engineer

We're seeking an experienced Lead AI Engineer to architect and build our next-generation healthcare AI platform powered by agentic workflows. You'll design multi-agent systems that help patients manage medications, schedule appointments, and access medical information through intelligent AI agents—while maintaining the highest standards of safety and compliance in healthcare AI.

This is a hands-on technical leadership role where you'll write code, make architectural decisions, and guide the technical direction of our AI products.

What You'll Build

• Healthcare AI Agents

  : Intelligent systems that help patients with medication management, appointment scheduling, and medical information access

• Multi-Agent Workflows

  : Orchestrated AI agents that collaborate to handle complex healthcare tasks (symptom assessment, medication reminders, care coordination)

• Agentic AI Systems

  : Autonomous agents that reason, plan, and execute actions using frameworks like LangGraph, CrewAI, or AutoGen

• RAG Pipelines

  : Medical knowledge retrieval systems that provide accurate, cited information from trusted sources

• Safety Systems

  : Guardrails and validation layers to prevent harmful medical advice and ensure regulatory compliance

Required Experience

Core Requirements (Must Have)

• 3-5+ years

  building production AI/ML systems

• 1-2+ years

  hands-on with LLMs and GenAI applications

• Proven experience

  with agent frameworks (LangChain, LangGraph, CrewAI, or similar)

• Production RAG systems

  : You've built and deployed retrieval-augmented generation pipelines at scale

• Multi-agent orchestration

  : You've designed systems where multiple AI agents work together
• Strong

  Python

  programming (you'll write a lot of code)

Agent Framework Expertise (Critical)

You should be comfortable with:

• Building agents with tools/function calling
• State management in multi-turn conversations
• Agent orchestration patterns (ReAct, Plan-and-Execute, etc.)
• LangGraph state graphs or equivalent frameworks
• Memory systems and context management
• Agent-to-agent communication and coordination

Technical Skills

AI/ML Frameworks:

• LangChain, LangGraph, CrewAI, AutoGen (at least 2 of these)
• OpenAI API, Anthropic Claude, or other LLM providers
• Vector databases (Pinecone, Qdrant, Weaviate, or similar)
• Prompt engineering and optimization

Backend & Infrastructure:

• FastAPI or similar frameworks for API development
• Docker, Kubernetes for containerization
• Cloud platforms (AWS, Azure, or GCP)
• Database design (PostgreSQL, MongoDB)
• CI/CD pipelines
• WebSocket or real-time communication protocols

Evaluation & Monitoring:

• LLM observability tools (Langfuse, LangSmith, etc.)
• RAG evaluation frameworks (RAGAS or similar)
• A/B testing and experimentation
• Production monitoring and alerting

Strongly Preferred

• Healthcare domain experience

  : You've built AI for healthcare, understand compliance requirements (HIPAA, GDPR), and know the stakes

• Fine-tuning experience

  : You've customized models for domain-specific tasks

• Low-latency systems

  : You've optimized agent response times for production

• Team leadership

  : You've mentored junior engineers or led technical initiatives

• Knowledge graphs

  : Experience integrating structured medical knowledge with LLM agents