Lead AI Engineer (Agentic Systems)
Core
Architect and build production-grade autonomous AI workflows (Agentic Systems) capable of reasoning, planning, and executing complex tasks independently.
Role type
Lead AI Engineer (Agentic Systems)
Builds
Multi-agent workflows, agent-to-agent communication protocols, and scalable autonomous decision-making systems.
Domain
Artificial Intelligence / Machine Learning / Software Engineering
Deliverable
production ML models
Required skills
Python, LLM orchestration frameworks (LangGraph, CrewAI, AutoGen), Vector Databases, Kubernetes, Docker, Data Pipeline Engineering, System Architecture, LLMOps, Model Optimization
Preferred skills
NLP, Knowledge Graphs, Graph Machine Learning, Real-time Operations, Human-in-the-Loop design
Technologies
LangGraph, CrewAI, AutoGen, LiteLLM, Langfuse, AWS AgentCore, Pinecone, Weaviate, Qdrant, PostgreSQL, DynamoDB, Databricks, Snowflake, Neo4j, AWS Neptune
Responsibilities
Architect multi-agent workflows and A2A communication protocols; Engineer state management and orchestration for non-deterministic agents; Build high-throughput data ingestion pipelines for real-time context; Implement observability, safety guardrails, and evaluation pipelines; Define technical roadmap and mentor engineering team.
Seniority
Senior, hands-on IC with leadership responsibilities