Job Description

We’re looking for a highly curious and hands-on AI Engineer to help us build and continuously improve intelligent workflows inside our product. This role sits at the intersection of model experimentation, AI-first product thinking, and full-stack implementation.

You’ll work closely with the founders to prototype, integrate, and optimize the use of LLMs and other AI systems across our platform. This is a technical, creative, and fast-moving role ideal for someone who thrives in an experimental environment and uses AI tools daily.

What You’ll Do

• Prototype and implement intelligent workflows powered by foundation models (OpenAI, Claude, Gemini, etc.)
• Explore and integrate multi-step reasoning using Chain-of-Thought and agent-style patterns
• Fine-tune open-source models or run prompt tuning experiments to improve task accuracy
• Use tools like Cursor and Windsurf to prototype and iterate quickly on product
• Work across the stack to integrate AI features (Node.js + Supabase + React)
• Run micro-model evaluations to test hypothesis-to-output cycles
• Use AI to augment your own workflow and automate internal tooling
• Contribute to our experimentation engine for evaluating which models to use where
• Implement AI Voice agents

Requirements

Required qualifications:

• Experience working with foundation models (OpenAI, Gemini, Claude, Mistral, etc.)
• Deep understanding of prompt engineering, reasoning chains, agent orchestration, and tool calling
• Hands-on experience with model fine-tuning and working with vector stores
• Proficiency in Cursor or Windsurf (daily usage preferred)
• Strong backend knowledge (Node.js, Supabase/Postgres)
• Comfort building UI flows (React)
• Passion for using AI not just as a tool, but as a core capability in product design
• Startup mentality: low ego, resourceful, and fast-paced

Preferred qualifications:

• Experience working with LiveKit or real-time communication platforms
• Exposure to LangChain, LlamaIndex, or similar agent frameworks
• Background in applied ML or RAG systems
• Product-minded engineer, understands the “why” behind features and contributes to UX/feature design
• Experience translating abstract AI capabilities into intuitive product workflows

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