Daivtech

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