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monday.com

AI Engineer (render.ai)

Tel Aviv

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hirly's read of this role

Seniority
Mid level
Country
IL
Work mode
On-site / unstated
First seen by hirly
28 Sept 2026

Derived automatically from the posting. Upload your resume above to see how the role scores against it.

the posting

Meet render.ai, monday.com 's new AI venture. At render.ai , we're redefining how humans use AI for work. 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 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

Original posting on monday.com's site ↗

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