# AI Engineer > EQL Tech · Phoenix, United States · — · Posted 2026-04-14 **Salary:** USD 130,000–200,000 **Workplace:** on_site **Department:** Engineering, Product & Tech ## Description ### 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 proud to represent **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 (known as ESAs or School Choice Funds). The $900B US Public Education budget is being opened up for parents to take control of their portion, which averages $7.5k per kid per year. Ambitious homeschool parents are already using these funds to piece together their dream education experience. Helping them access these funds is Step 1 in the journey to build the next-gen education system. The company treats this as their life's work and has already rejected an acquisition offer because they care about this being done right. ### **The Team** You will be joining an in-person company, working together in the office. - **The Founders:** The founders are engineers who have run their own alternative school together. One previously worked as a Quant at Goldman Sachs, and the other built the computer vision system for the largest smart warehousing company globally, serving 1M customers/day at age 19. - **The Core Team:** You will work alongside top talent, including a founding engineer who did AI research at MILA and at Elon Musk’s SpaceX school, a Head of Risk from Mercury, Stripe, and Circle, and a Payments Engineer from Microsoft and Goldman Sachs. The team also includes the former Deputy Director at Arizona's ESA department and leading school choice advocates. ### **The Role: AI Engineer** As AI Engineer, you will work directly under the Head of AI — a researcher with experience at one of the world's leading ML research labs — to build and ship the intelligence layer that powers the product. AI is not a feature here; it is the core of how families get instant eligibility decisions, and how the company scales compliance without scaling headcount. You will own AI products end-to-end, from first 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 minimal hand-holding and a high bar for quality - **Optimise accuracy and latency:** tune LLM and VLM pipelines, and classical ML models where appropriate, to meet the standards a regulated fintech product demands - **Create robust evals:** build evaluation frameworks that make AI behaviour measurable, reproducible, and improvable over time — so regressions are caught before users feel them - **Read data and fix mistakes:** diagnose real-world AI failures by going directly into the data, making ad-hoc corrections, and closing the loop fast - **Build endpoints and tooling:** surface AI capabilities to teammates in reliable, well-documented ways so the whole team can move faster without depending on you for every query - **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 individual products mature and optimisation demands it ## Requirements ### **Your Profile** - **Biased toward simplicity:** you know that managing many AIs gets complex fast — you resist unnecessary abstraction and build systems that are easy to reason about and maintain - **Values old and new AI equally:** you recognise the tradeoffs between prompting, fine-tuning, and training from scratch — and you pick the right tool for the job rather than defaulting to the latest trend - **User-obsessed:** AI is the blocker to a good number of AHA moments in the product — you keep the end-user in mind in every technical decision, not just the benchmark - **No task beneath you:** reading data, making database edits to correct AI mistakes, writing evals for edge cases — you treat this as essential product work, not a distraction from "real" engineering - **Comfortable with ambiguity:** you can scope your own work, define your own quality bar, and ship without waiting to be unblocked - Able to work in-person with the team 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 ### **Commitment, Compensation & Benefits** This will be a big commitment, and we're aiming high. It needs to be something you are energised about taking on, or this isn't the team for you. - **Competitive Salary:** $125,000 – $175,000 per year, commensurate with experience. - **Generous Founding Equity:** We compensate you well with equity. - **Top-Tier Backing:** We've raised $16M from top-tier VCs and angels. - **Relocation Support:** You are willing to relocate to San Francisco, CA, or Phoenix, AZ, and travel to visit customers. We're an in-person company and are in the office together. - **Comprehensive Visa Sponsorship:** If you do not have a visa, we can support you. - **Unmatched Impact:** The rare opportunity to directly shape how the $900B US Public Education budget is being opened up for parents to take control of their portion (avg. $7.5k/kid/year). ## Apply [Apply at EQL Tech](https://apply.workable.com/eqltech/j/DF975F151B/apply) --- Powered by [Workable](https://www.workable.com)