AI Engineer

About the company

Cambio offers an AI-native platform that ingests and analyzes unstructured building data so commercial real-estate owners and investors can quickly identify retrofits, ensure regulatory compliance, and optimize capital planning.

About this role

ABOUT CAMBIO Cambio is a software platform for real estate decarbonization. We help commercial real estate owners bring their portfolios to net-zero with an AI-driven sustainability, asset, and investment management platform. We're backed by Y Combinator, Google, and Stanford — and we're the fastest-growing startup in our category. THE ROLE We're looking for an AI Engineer to build AI-powered features, help teammates do their best work, and have fun doing it. WHAT YOU'LL BE DOING - Build AI features end-to-end, from prototype to production - Design and run evals to measure and improve model/feature quality - Build and maintain data + inference pipelines that power AI features in production - Experiment with new models, prompting, and retrieval approaches to improve accuracy and cost - Support and collaborate with your teammates WHO YOU ARE - An A-player: low ego, curious, and serious about your craft - You are outcome driven - Work isn't in opposition to life for you - it's part of your life because you genuinely enjoy it - You ship through obstacles — roadblocks are part of the problem to solve - You move with urgency and close the week with visible impact - You're relentlessly curious and treat truth-seeking as a discipline - You believe iteration speed is quality - the way to build great things is to build fast and learn faster - You show up for your teammates, in person. You unblock before being asked and never let someone stay stuck - You own your work end-to-end - proactive about visibility, proud of your progress, and you over-communicate until everyone is fully aligned WHAT DO YOU BRING - Experienced in Python web development (Django is a bonus) - Someone who's shipped AI features and understands the eval challenges that come with them - Hands-on experience with LLMs/generative AI (prompting, fine-tuning, or RAG) - Comfortable with evaluation frameworks and measuring model quality in production - Familiar with vector databases and retrieval-based architectures - Understands the tradeoffs between model cost, latency, and accuracy WHAT WE OFFER - Competitive compensation and startup equity - Flexible time off - $1,200 annual learning budget - Catered lunch - Best workstation in beautiful offices in Waterloo, New York, and San Francisco

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