Senior AI Product Engineer

Klarity•San Francisco, CA

3d•Hybrid

About The Position

Klarity is a fast-growing Series B company that has raised $91M and experienced 7x growth last year. We are building the AI Transformation, which is expected to be 10x bigger than the digital transformation industry. Our AI discovers how work happens across teams and applications, structures it into a living Context Graph, and improves it continuously. Leading companies like ServiceNow, DoorDash, OpenAI, Google, and Stripe use Klarity to transform their operations. We are looking for an AI Product Engineer who combines product thinking with technical execution, responsible for defining and building features from customer insight to production deployment.

Requirements

Strong product instincts grounded in user research and customer conversations.
Technical depth (CS fundamentals, React, TypeScript, Python) allowing for prototyping, evaluating tradeoffs, and shipping MVPs independently.
Experience shipping AI-native features to production, understanding product tradeoffs related to non-determinism, AI value, and user expectations for probabilistic systems.
Ability to use AI coding assistants (like Cursor, Claude Code, Replit) for rapid prototyping and testing product directions.
Experience defining success metrics, talking to users, analyzing data, and iterating based on learnings.
Ability to pivot quickly when something isn't working and double down when traction is found.
Enthusiasm for building products people love and raising the bar for the team.

Nice To Haves

Strong UX sensibility and visual taste, with the ability to make informed decisions about user flows, information architecture, and interactions.
Comfortable running user interviews and asking tough questions.

Responsibilities

Own product features end-to-end, including understanding customer problems, defining product and UX, scoping MVPs, shipping to production, measuring results, and iterating.
Build and ship rapidly by writing code across the full stack and using AI tools to accelerate development.
Bridge AI capabilities with user needs by partnering with engineers and AI researchers to translate possibilities into product experiences.
Define product strategy through experimentation, using rapid prototyping and user testing to inform product direction.
Ship MVPs to learn fast, then iterate based on real user feedback and data.
Identify where cutting-edge AI can create step-change value versus where simpler solutions win.