AI Engineer

Location San Francisco, CA or Phoenix, AZ (In-Office) Partnership EQL Tech has been exclusively retained by a high‑growth technology startup to appoint a mission‑critical AI Engineer to own the brand feel of the company and the movement they're building. About The Company & The Mission EQL Tech is a highly ambitious, well‑funded startup that has raised $16M from top‑tier VCs and angels. The company is building the financial rails to help families access new State education funds (ESAs or School Choice Funds). The U.S. public education budget is $900B, and parents can take control of their portion, averaging $7.5k per child per year. Ambitious homeschool parents already use these funds to create their dream education experience. The Team Founders: Engineers with experience running an alternative school, a former Goldman Sachs Quant, and a senior computer vision engineer who served 1M customers/day. Core Team: Includes a founding engineer who did AI research at MILA and at Elon Musk’s SpaceX school, a Head of Risk from Mercury/Stripe/Circle, a payments engineer from Microsoft and Goldman Sachs, and former Deputy Director at Arizona’s ESA department. The Role: AI Engineer As AI Engineer you will work directly under the Head of AI to build and ship the intelligence layer that powers the product. AI is the core of how families receive instant eligibility decisions and how the company scales compliance without scaling headcount. You will own AI products end‑to‑end, from prototype to production. As AI Engineer, you will Build MVPs from scratch: take new AI products from zero to real users—both consumer‑facing and internal tooling—with a high bar for quality. Optimize accuracy and latency: tune LLM and VLM pipelines and classical ML models to meet the standards of a regulated fintech product. Create robust evaluations: build evaluation frameworks that make AI behavior measurable, reproducible, and improvable over time. Read data and fix mistakes: diagnose real‑world AI failures, make ad‑hoc corrections, and close the loop fast. Build endpoints and tooling: surface AI capabilities to teammates in reliable, well‑documented ways so the team can move faster. Work across the full AI stack: primarily LLM and VLM‑based in early stages, with scope to fine‑tune or train models from scratch as product demands it. Requirements Bias toward simplicity and resist unnecessary abstraction. Value both old and new AI techniques, choosing the right tool rather than chasing trends. User‑obsessed: keep end‑user in mind in every technical decision. No task beneath you: reading data, editing databases, writing evaluations are essential product work. Comfortable with ambiguity: scope work, define quality bar, and ship without waiting to be unblocked. Able to work in‑person in San Francisco, CA or Phoenix, AZ (visa support available). Experience with LLM APIs, vector databases, fine‑tuning pipelines, or evaluation frameworks is a strong plus. Benefits Generous founding equity. Top‑tier backing from $16M raised by top‑tier VCs and angels. Relocation support to San Francisco, CA or Phoenix, AZ. Comprehensive visa sponsorship. Unmatched impact on the $900B U.S. public education budget. #J-18808-Ljbffr EQL Tech (sales & engineering talent)