The opportunity
We’re looking for an AI Applications Engineer to help drive Notion’s business transformation efforts. In this role, you’ll be a strategic partner to our internal stakeholders (primarily GTM, Finance and People teams) and deliver and scale creative AI-driven solutions to…
What you'll do
Work with stakeholders to discover opportunities from ambiguous problem: statements, translate them into scoped solutions, and drive iterative releases from idea to adoption
Build and ship end‑to‑end AI solutions—from problem framing through data: readiness, modeling, evaluation, and production rollout
Establish evaluation and production-readiness patterns (metrics, monitoring,: human-in-the-loop, rollout plans) so solutions are reliable at scale
Create reusable components, tooling, templates, and playbooks that accelerate: future projects and enable other teams to ship safely
years of experience as a Software Engineer or Data Engineer (or equivalent),: with a track record of building and operating production systems end-to-end across application code, data, and infrastructure. Domain experience partnering with GTM and Finance is a plus.
Experience building AI-enabled applications in production (LLMs and/or: classical ML), including prompt + tool orchestration, retrieval, evaluation, and iteration based on real-world feedback.
What they're looking for
- Strong production-readiness instincts, including observability, monitoring,: quality gates, incident response, and safe rollouts/rollbacks in live business workflows.
- Systems and integration fluency across APIs, data pipelines, and enterprise: tools (e.g., CRM, finance, ticketing, HRIS), with the ability to navigate messy systems and still deliver reliable outcomes.
- Impact-driven approach to technology: You use technology to drive measurable user and business outcomes, not as an end in itself. You stay current with tools like Cursor, Claude Code, and other AI-assisted development environments, and you’re pragmatic about choosing what delivers the most value.
- Thoughtful problem-solving: You start with a clear understanding of context, align technical and non-technical partners, and translate AI concepts into actionable business outcomes. You navigate ambiguity and decompose complex problems into clean solutions.
