Software Engineer, AI Capture

Notion
San Francisco2026-04-21Hybrid

About the job

Build the most advanced AI Meeting Notes product — and expand it into broader “AI data capture” features that help teams turn conversations into durable context, tasks, and knowledge. Our mission is to 10x the rate of business context & data that enters Notion — optimized for agents — so teams get superhuman memory across workstreams and customers. Notion workspaces that use AI Meeting Notes already enter 6x more data on a daily basis, so we’re well on our way.

Responsibilities

- Ship end-to-end product experiences across capture → transcript → summary → follow-ups (full-stack ownership).

- Make meeting & data capture feel effortless and magical (e.g., speaker identification via audio waveforms, richer in-meeting UX, smarter organization).

- Improve summary quality that teams trust: structure, factuality, and citations that make downstream agents and humans more capable.

- Raise the bar on reliability & observability across the pipeline (SLOs, debugging workflows, incident response) for realtime systems.

- Build agentic meeting workflows that turn discussions into tasks, follow-ups, and organized knowledge — so “we talk and things get done.”

- Deliver enterprise readiness: sharing/permissions, compliance, and scalability for our fastest-growing customers.

Qualifications

Minimum

- 10+ years shipping production software, with a strong track record of owning features end-to-end

- Strong full-stack engineering skills (frontend + backend) and excitement to own user-facing product end-to-end.

- Product-minded craftsmanship: you sweat details, iterate quickly, and use data and user feedback to guide decisions.

- Experience building and operating production systems (debugging, on-call/incident response, performance, and reliability).

- Ability to work across ambiguous problem spaces, align stakeholders, and drive execution with high ownership.

Preferred

- Experience with LLM / applied AI product development (prompting, evals, model integrations, or quality measurement).

- Experience with media / realtime pipelines (audio, transcription, diarization, streaming, low-latency processing).

- Experience building for enterprise customers (permissions models, compliance, scale, and security).