Engineering Team Lead - Agentic System

Monday.com Monday.com · Enterprise · Tel-Aviv, Israel · Tech & AI

Engineering Team Lead for an 'Agentic OS' group focused on building a unified agent architecture for enterprise-level AI services. The role involves owning the data, knowledge, and context layers, building scalable data ingestion pipelines, leading development of state-awareness and memory infrastructure, designing orchestration and middleware for multi-agent collaboration, and managing an AI-native engineering team. Requires experience in platform engineering, distributed systems, data pipelines, RAG at scale, LLM orchestration, and taking AI products to production.

What you'd actually do

  1. Own the architecture and roadmap of the Knowledge & Context platform
  2. Build scalable data ingestion pipelines (Gong, Slack, internal systems, etc.)
  3. Lead the development of our state-awareness and memory infrastructure
  4. Design orchestration and middleware for multi-agent collaboration
  5. Manage and mentor a high-performing, AI-native engineering team

Skills

Required

  • 3 years of experience leading engineers while remaining deeply technical
  • Strong background in platform engineering, distributed systems, and data pipelines
  • Hands-on experience with RAG at scale and LLM orchestration frameworks (LangChain, LangGraph, or similar)
  • Proven track record of taking AI products from prototype to production
  • Ability to translate complex architecture into clear execution plans
  • Business-oriented mindset with strong Product partnership

What the JD emphasized

  • own the Data, Knowledge, and Context layers
  • translating agentic strategy into scalable, production-grade systems
  • build the orchestration engine
  • state-awareness and persistent memory
  • RAG at scale
  • LLM orchestration frameworks
  • taking AI products from prototype to production

Other signals

  • Agentic OS
  • unified agent architecture
  • enterprise-level service through AI
  • Knowledge & Context platform
  • state-awareness and persistent memory
  • orchestration engine
  • multi-agent collaboration
  • AI products from prototype to production
  • RAG at scale
  • LLM orchestration frameworks