Senior AI Engineer
Daivtech
Job Description
We're seeking an experienced Senior 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 agent
Required Skills
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