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render.ai, a new AI venture from monday.com, is seeking a Senior AI Engineer to join a small, autonomous team operating with early-stage startup spirit. The role focuses on redefining how humans use AI for work by enabling users to bring ideas to life in minutes using natural language.
You will own the model quality lifecycle end-to-end, from early experiments through production monitoring. This includes prompt engineering for LLMs and image generation models, building evaluation frameworks and offline tests, and running A/B experiments to drive measurable improvements. You'll monitor live AI systems for latency, hallucinations, and drift, proactively identifying and addressing failure modes before they impact users.
The role requires strong proficiency in both TypeScript and Python, with the ability to move fluidly between rapid AI experimentation and solid production engineering. You'll work hands-on with data—sourcing, cleaning, and optimizing it to improve prompts, models, and evaluations. The environment is fast-moving and ambiguous; you'll help shape the product direction, not just execute a fixed roadmap. You'll stay current with frontier AI techniques and models, and contribute to expanding render.ai into new modalities like voice and video.
This is a high-impact role where every engineer influences product strategy and architecture. You'll be part of a team that values curiosity, ownership, and the ability to thrive in uncertainty.
Requirements:
- Strong proficiency in TypeScript and Python
- Deep experience with prompt engineering for LLMs and image generation
- Proven ability to build and maintain evaluation frameworks, offline tests, and A/B experiments
- Experience monitoring and optimizing live AI systems (latency, hallucinations, drift)
- Hands-on data sourcing and cleaning skills
- Comfort with ambiguity and fast-moving environments
- Genuine interest in frontier AI models and techniques
Advantages:
- Experience with modern LLMs and image models (Flux, Imagen, or similar)
- Background building AI-native or agent-based products from scratch
- Familiarity with LLM observability tools, tracing, and debugging workflows
- Track record in rapid prototyping, experimentation, or startup environments
