AI Engineer – New Ventures

Monday.com Monday.com · Enterprise · Tel-Aviv, Israel · R&D

AI Engineer at Monday.com's New Ventures team, focusing on building AI-native products from scratch. The role involves architecting and implementing autonomous agents, agent orchestration frameworks, and owning the full lifecycle of model quality, including experimentation, evaluation, and production monitoring. Requires strong software engineering skills and experience with LLM tooling, RAG, vector databases, and agent-based systems.

What you'd actually do

  1. Architect and build AI-native systems from 0→1, including autonomous agents and intelligent workflows
  2. Design and implement agent orchestration frameworks (memory, planning, tool usage, self-reflection, and recovery)
  3. Own the full lifecycle of model quality—from experimentation and evaluation to production monitoring and continuous improvement
  4. Design and build evaluation frameworks (offline benchmarks, online experiments, A/B testing) to guide model and product decisions
  5. Monitor production AI systems, tracking quality, latency, cost, and failure modes (e.g., hallucinations, drift), and drive iterative improvements

Skills

Required

  • Proven experience building and deploying production-grade AI systems
  • Strong software engineering foundation with 4+ years of experience in backend or full-stack development
  • Deep familiarity with modern AI tooling and ecosystems (LLM APIs, embeddings, vector databases, RAG pipelines)
  • Hands-on experience designing evaluation and monitoring systems for LLM-based applications in production
  • Experience designing or working with agent-based systems (e.g., ReAct, tool use, multi-step reasoning loops)
  • Strong understanding of system design, scalability, and reliability in distributed environments
  • Experience running structured experiments (e.g., A/B tests, prompt/model comparisons) and using data to drive decisions
  • Ability to navigate ambiguity and rapidly evolving technologies
  • Strong communication skills and a collaborative, product-oriented mindset

Nice to have

  • Experience building AI-native or agent-based products from scratch
  • Familiarity with LLM observability tools, tracing, and debugging workflows
  • Experience with real-time systems, WebSockets, or collaborative environments
  • Background in rapid prototyping, experimentation, or startup-like environments

What the JD emphasized

  • Own the full lifecycle of model quality
  • model quality, evaluation, and continuous improvement in production
  • evaluation frameworks
  • Monitor production AI systems
  • evaluation and monitoring systems for LLM-based applications in production
  • agent-based systems
  • structured experiments

Other signals

  • building AI-native products
  • agent architectures
  • model quality and evaluation
  • production monitoring