Full Stack Engineer

Hey, we are Deepnote! 👋 We help data teams solve the hardest problems. Achieving this requires more than just advanced algorithms, larger datasets, and greater computing power. We need powerful tools that don’t yet exist. We need to invent them first.

As the best rated data notebook platform in the world, we are proud to have clients like Coca Cola, SoundCloud, NASA, Gusto, Webflow, Ramp, Harvard University, and hundreds more. As we build out our core team, we're seeking kind, curious and talented individuals ready to grow with us and shape the future of data science.

You'll work on some of the most difficult problems in the field - we don't expect you to be an expert on everything, but we do expect you to learn fast and take a lead. You'll be responsible for crafting beautiful and efficient code, gathering user feedback, and designing comprehensive workflows. You'll become a specialist in data science tooling, with the autonomy to decide on the technologies we use and the features we implement.

• A Deepnote Engineer is an end-to-end owner of a project, from initiative to planning, delivery, and tracking.

• Full ownership and trust are the daily bread and butter. Engineers at Deepnote help data teams solve the hardest problems by actually dealing with the most challenging engineering issues themselves.

• Every day is a new technical and product challenge that has not been cracked before, and being proactive and creative with solutions is a must-have.

• Typescript, React, GraphQL

• Node.js, PostgreSQL, Redis

• Kubernetes, AWS

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  Build new features across the stack — backend logic, APIs, and polished UI components.

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  Design and iterate on AI-powered features (chatbots, copilots, code generation, agents).

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  Work with prompts, evaluations, and context handling to deliver reliable AI features.

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  Enhance our real-time collaborative notebook experience.

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  Think data-first: structure, transform, and route information through the product.

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  Support and learn from our vibrant community of data scientists and developers.

• You’re strong in full-stack product engineering (TypeScript, React, NodeJS, GraphQL, PostgreSQL).

• You’ve got hands-on experience with AI/LLM products (chatbots, assistants, or AI-powered features), and you’re comfortable — even excited — when it comes to designing prompts, talking to AI models, and getting the most out of them.

• You understand the basics of how LLMs work: tokenization, memory/context limits, and the trade-offs between cost, latency, and quality.

• You have a data-oriented mindset — thinking naturally about how information flows through a product — and you know how to make that thinking practical.

• Most importantly: you’re the kind of engineer who learns fast, ships fast, understands urgency, and stands fully behind the work you deliver.