Software Engineer, Early Career (AI)

Who We Are Notion is the collaborative AI workspace where teams and agents think together. We're building one place where your knowledge, projects, meetings, and AI tools live side by side, so work is faster, clearer, and less fragmented. Millions of individuals, small teams, and large companies run their work on Notion. Notinos (our employees) are customer zero in bringing this future of work to life. We care about craft, building things that last, and the belief that great work is still fundamentally human. Our goal isn’t to ship the next feature. Each and every team of Notinos is working to set the standard for how humans work together in the AI era. From building a business’s system of record to making and managing AI agents to automating away the busy work, we care deeply about giving our customers more time for their life’s work. About the Role As an engineer at Notion, you’ll help shape core user experiences and accelerate how people discover value in Notion. You'll tackle meaningful challenges with increasing autonomy, crafting code that millions of users will experience. You'll take ownership of projects that matter, make critical technical decisions, and contribute your unique perspective to our product vision. Working alongside passionate experts across design, product, and data, you'll help shape the future of how people work. We're looking for an Early Career AI Engineer to join as a strategic partner in shaping Notion's AI vision. You'll work on cutting-edge AI-powered features, leveraging LLMs, embeddings, and other AI technologies to make Notion more intelligent and capable. This role may be aligned to one of multiple AI-focused teams at Notion. Depending on team match and business needs, you could work on: - AI product engineering: building model-powered features end-to-end (UX, APIs, retrieval, orchestration, quality, and reliability) - Model & systems engineering: improving model integration and performance (latency, cost, safety, robustness) and building the infrastructure that supports model serving and experimentation - Evaluation & quality (evals): creating evaluation frameworks and automated/ human-in-the-loop testing to measure and improve model and product quality What You’ll Achieve - Partner with your team to prototype and ship an AI-powered product improvement - Own a scoped productionization project: integrate a new model/technique into an existing workflow, add monitoring + guardrails, or improve latency/cost/reliability. - Contribute to evals and iteration loops: build or extend an evaluation set, run experiments, analyze results, and translate learnings into product or system changes. Skills You'll Need to Bring - You have less than two years of engineering experience. You have solid fundamentals in data structures, algorithms, and distributed systems, with a customer-minded, pragmatic approach to solving problems. - Expertise building and prototyping: You’re excited to build and iterate quickly, and you’ve started exploring AI/ML through coursework, projects, internships, or hackathons. You’re comfortable learning how different parts of a product fit together (UI, APIs, data), have some familiarity with relational databases like Postgres or MySQL, and can take an idea from prototype to a working feature with guidance. - Thoughtful problem-solving: You approach problems holistically, starting with a clear and accurate understanding of the context. You think about the implications of what you're building and how it will impact real people's lives. You can navigate ambiguity successfully, decompose complex problems into clean solutions, while also balancing the business impact of what you’re building. - Impact-driven approach to technology: You see technologies as tools to achieve user impact rather than ends in themselves. You care more about building successful systems that solve real problems than about using specific tech stacks or following trends. You stay current with the latest tools like Cursor, Claude Code, and other AI-assisted development environments, you're pragmatic about choosing the right tool for the job, focusing on what delivers the most value to users and the business. - Proactive communication and high agency: You own your work, communicating clearly about progress and blockers. You don't wait for instructions for every step but rather show initiative in identifying what needs to be done and driving projects forward. You ask questions when needed while independently finding solutions to problems. Nice to Haves - You have experience with any part of our technology stack: React, TypeScript, Node.js, Postgres, and Elasticsearch. - You care about the interaction between technology and society, the ways in which they inform each other, and our responsibility as technologists to be conscious of that relationship. - You've heard of computing pioneers like Ada Lovelace, Douglas Engelbart, Alan Kay, and others—and understand why we're big fans o

Less than two years of engineering experience. Solid fundamentals in data structures, algorithms, and distributed systems, with a customer-minded, pragmatic approach to solving problems. Expertise building and prototyping: excited to build and iterate quickly, started exploring AI/ML through coursework, projects, internships, or hackathons. Comfortable learning how different parts of a product fit together (UI, APIs, data), familiarity with relational databases like Postgres or MySQL, and can take an idea from prototype to a working feature with guidance. Thoughtful problem-solving: approach problems holistically, understand context, consider implications, navigate ambiguity, decompose complex problems into clean solutions while balancing business impact. Impact-driven approach to technology: focus on user impact over tech stacks. Stay current with tools like Cursor, Claude Code, and other AI-assisted development environments. Proactive communication and high agency: own work, communicate progress and blockers, take initiative, ask questions when needed while independently solving problems.