Lead AI Engineer

About the job

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.

Requirements

• AI
• Machine Learning
• Python
• GenAI
• Healthcare
• Multi-Agent Systems

Preferred Technologies

• AI
• Machine Learning
• Python
• GenAI
• Healthcare
• Multi-Agent Systems