AI Engineer (render.ai)

Hybrid
Companymonday
LocationTel Aviv
CategoryData & AI
DepartmentRender
Seniority-
WorkplaceHybrid
Posted2026-09-07
Estimated salary₪28K–45K (a market estimate, not the employer's figure)
Viaashby

Description

Meet render.ai, monday.com http://Monday.com's new AI venture. At render.ai http://render.ai, we're redefining how humans use AI for work. render.ai http://render.ai enables anyone to bring ideas to life in minutes, using their words. We're a small, autonomous team - closer in spirit to an early-stage startup than to an established company. There's no fixed playbook: we're still figuring out what the product looks like, and every engineer helps shape that, not just build it.

What are we looking for?

  • You love prompt engineering for LLM and image generation, chasing high-fidelity outputs at scale, and you know how to push foundation models further than most think possible
  • You own the model quality lifecycle end-to-end, from early experiments to production monitoring, turning the latest LLM breakthroughs into systems that hold up at scale
  • You build evaluation frameworks you can trust, offline tests, and A/B experiments that turn feedback into real, measurable improvements
  • You keep a close eye on live AI systems, watching latency, hallucinations, and drift, and get ahead of failure modes before they become real problems
  • You're genuinely strong in TypeScript and Python, comfortable moving between fast AI experimentation and solid production engineering
  • You like getting hands-on with data, sourcing and cleaning it to make prompts, models, and evals better
  • You're energized by ambiguity and fast-moving environments, always curious about the newest models and techniques on the frontier
  • You're excited about where this goes next, helping render.ai http://render.ai expand into new modalities like voice and video

Advantages:

  • Experience with modern LLMs and image models such as Flux and Imagen
  • Experience building AI-native or agent-based products from scratch
  • Familiarity with LLM observability tools, tracing, and debugging workflows
  • Background in rapid prototyping, experimentation, or startup-like environments