Senior AI Product Engineer
Seeking a Senior AI Product Engineer to build full-stack features, explore AI frontiers, and own product development, requiring experience with Python, React, and LLMs.
We’re looking for an excellent product builder to join us - someone who’s as excited as we are to build the next generation of UX and bring it to millions of users.
What will you be doing?
- Owning the product: Our team is hyper-focused on building a great product - this includes using the product, listening to customer feedback, and surfacing ideas for where we can improve. There’s no engineering vs. product fences here - everyone is a product owner.
- Shipping features: Own full-stack features end-to-end: from ideation to design to implementation.
- Exploring the frontier: AI is constantly evolving - you’ll be testing out new models, techniques and libraries to chart the path forward.
Examples of everyday work:
- Pair with our AI Engineering Lead to debug why an agent gave out a bad answer — and design a clever retrieval fix that solves the edge case.
- Build a pipeline that automatically spots blind spots in a knowledge base and automatically fills in the missing piece.
- Experiment with new frontier models and libraries, then present back to the team on what’s hype vs. what we should ship next.
- Jump into a customer debug session with a PM, see how an agent failed in the wild, and ship a fix that same day.
Requirements
- Experience building full-stack features and applications
- Experience with relevant technologies (We use Python on the backend and React for the frontend_)
- Strong product intuition - proactively identify improvements without being asked
- Comfort with moving fast and making smart tradeoffs
- Stellar ownership of features and code quality
- Familiarity with LLMs/AI - either from work or your own exploration
Bonus:
- You’ve been part of a small startup or skunkworks team and thrived in uncertainty
- You’ve built agents using frameworks like Pydantic AI
- You’ve worked deeply with TypeScript
- You’ve worked with applications built on Temporal
- You’ve built RAG pipelines before