Staff Engineer, Applied AI

Were a technology company building AI-native learning products used by more than seven million students worldwide alongside Honen our workforce-learning platform for organizations. Both run on the Learn Engine the intelligence that moves a learner from initial understanding to demonstrated mastery. We work with partners like NVIDIA to bring responsible learning-first AI to the students who need it most.

This is a founding-team role. Youll work directly with the people making the decisions own meaningful parts of the product and ship AI features that reach millions of learners not prototypes that stall at the demo stage.

Every learner deserves the chance to succeed. StudyFetch started with one idea: high-quality personalized learning should be within reach for anyone at any stage of life. Honen carries that belief into the workforce.

• Accessible to everyone. Learning should reach every person whatever their background role or resources.
• Meet people where they are. Every course adapts to a persons pace their level and the way they learn best.
• Learning never stops. From a first job to a new career people keep growing at every stage of life.

We hire people who share this conviction. The work is demanding and the hours can be long and what sustains you through it is caring whether a real student finally understands the material.

• Whole product surfaces end to end. The decision to build the architecture production and the on-call that follows. You own the outcome.
• AI and LLM features in the live product. Prompt and eval pipelines retrieval agent workflows and the demanding work of keeping latency cost and model behavior reliable for real users at scale.
• Full-stack work across web and mobile. You decide where the line between client server and model belongs and you stand behind it.
• The bar for the team. The patterns you set are the ones the rest of the team follows.

Youre a strong fit if either of these is true:

• 7 years building and shipping production software with real depth in fullstack and applied AI or
• You were a founding or early engineer who owned a significant share of a real product. Fewer years on paper but you took something from nothing to live users and can demonstrate it.

Beyond that:

• Youve shipped AI to production with real users not demos. This is the requirement that matters most. You can walk us through a feature you built what it did which parts were yours and what went wrong. Side projects and experiments are valuable but they are not the same as shipping to production.
• You use AI every day and have informed opinions about it. Genuine curiosity is the one thing we cant teach.
• Youve worked through launch crunch and know how you stay effective under pressure.
• Youre candid about tradeoffs. You can tell us what surprised you last time and what youd do differently.
• The mission is why youre here. What sustains you through the hard weeks is the learner on the other end the one who finally understands because of something you built.

You dont need every item below but you should be deep in most and able to ramp quickly on the rest:

• Frontend: React TypeScript Tailwind
• Backend: Express REST API design serverless k8s
• AI/LLM: LLM application development prompt engineering evals RAG agent workflows vllm
• Data: MongoDB and PostgreSQL; working knowledge of vector databases
• Cloud: GCP Cloudflare Vercel
• Mobile: React Native (iOS/Android)

• This is an in-person role at a fast pace with periods of intense work around major launches.
• Youll have significant ownership and autonomy with limited oversight. The role suits engineers who do their best work with room to run.
• Its a strong fit for engineers who have shipped production AI to real users. If your AI experience has been primarily tutorials or demos this likely isnt the right match.

• $170000$270000 base salary plus equity
• 100% employer-paid Medical Dental and Vision; 75% dependent coverage
• 401(k) with employer matching
• Daily team dinner provided in-office
• A small mission-driven team changing how the world learns

#LI-SF1

Required Experience:

Staff IC