Engineering Team Lead - Agentic System
Generate a McCoy IQ challenge in 30 seconds.
See how candidates think and approach the work this role demands, before the phone screen. We'll build a video challenge from this posting, and you can edit or share it before it goes live.
Key details
What makes this role novel
This role represents a new engineering leadership category focused specifically on building infrastructure for autonomous AI agents—a capability that has only become viable and commercially critical in the last 2-3 years with advances in LLMs and agentic frameworks.
Job Description
monday.com is the AI work platform powering the most ambitious teams. 250,000+ customers across departments use us to bring people, workflows, and AI agents together on one flexible platform where AI doesn't just assist, it executes. We move fast, build things that matter, and foster an ownership-driven culture where you're empowered to shape how organizations work and outpace their competition.
We are the Tech & AI group within Monday’s Customer organization, building the “Agentic OS” - a unified agent architecture that delivers enterprise-level service through AI.
As the Engineering Team Lead - Agentic System, you will own the Data, Knowledge, and Context layers that power our agents. This is the most senior engineering role in the group, responsible for translating agentic strategy into scalable, production-grade systems.
You will partner closely with Product to build the orchestration engine behind our AI agents, enabling true state-awareness and persistent memory across agents
About the role
Own the architecture and roadmap of the Knowledge & Context platform
Build scalable data ingestion pipelines (Gong, Slack, internal systems, etc.)
Lead the development of our state-awareness and memory infrastructure
Design orchestration and middleware for multi-agent collaboration
Manage and mentor a high-performing, AI-native engineering team
Serve as the technical authority in cross-functional decision-making
Requirements
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
Audit details(provenance, verification trail, raw fields)
Core fields
monday:864ebdd5-e7c2-4e62-bb4b-9c65f54cdceeProvenance
mondayVerification trail
This posting hasn't been probed by our closure verifier yet. Stream C runs on a rolling schedule against postings approaching the close-decision threshold.
LLM enrichment
See how we measure for definitions, or our corrections log for known issues. Found something wrong? Flag a correction.