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Senior AI Product Engineer | Notion | SF · Ganloss

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AI role · Open offer

Senior AI Product Engineer

Notion

Full-time
Senior
AI product
Hybrid
685 Market Street, San Francisco, CA 94105, United States · Hybrid
San Francisco, United States
$170k–$230k + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

3 skills1 tool

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: 685 Market Street, San Francisco, CA 94105, United States · Hybrid
Compensation: $170k–$230k + equity
Experience level: Senior
Team: AI product
Benefits & perks: Equity, wellness, hybrid SF.
How to apply: In-product AI feature with user metrics.
Company site: www.notion.so
Listed: Jun 16, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

Notion is hiring a Senior Senior AI Product Engineer on the AI product team (Hybrid · San Francisco, United States). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Notion embeds AI across docs, wikis, and workflows for teams globally. SF product engineering ships fast with strong craft and safety review.

Senior AI Product Engineer: in-editor assistants, tool routing, and enterprise privacy controls.

What you will do

Ship production product-embedded AI with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
Improve data quality, labeling, and offline metrics that correlate with business KPIs.
Document architectures and runbooks for on-call and customer-facing teams.
Mentor engineers on testing, observability, and responsible AI practices.

What we look for

Strong Python and modern ML/LLM stack experience with multiple shipped features.
Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
Pragmatic ownership from prototype to production—including cost and latency budgets.
Eligible to work in the listed country; professional English (French a plus for Paris roles).

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
OpenAI API
Calling frontier APIs with retries, cost controls, prompt versioning, and safety filters.
TypeScript
Practical TypeScript experience applied to LLM features, retrieval, agents, and evaluation in production or rigorous pilots.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

ReactTool
Regular use of React in the LLM & generative AI stack—configuration, debugging, and team conventions.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: In-product AI feature with user metrics.
Several of these show up in recent shipped work—not only on your CV: Python, OpenAI API, TypeScript, and React.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You are comfortable with the hybrid rhythm (Hybrid · San Francisco, United States)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: $170k–$230k + equity, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on My account, and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

In-product AI feature with user metrics.

Sign in with a candidate account to apply

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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