AI Engineer

EQL Tech (sales & engineering talent); San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Generous founding equity

Top-tier backing from investors

Relocation support

Comprehensive visa sponsorship

Opportunity to impact U.S. public education

Job summary

A high-growth technology startup in San Francisco seeks an AI Engineer to lead AI product development from prototype to production. The role involves optimizing model performance, creating robust evaluation frameworks, and troubleshooting real-world AI issues. Candidates should have experience with LLM APIs and a user-obsessed mindset. The company offers generous equity, relocation support, and comprehensive visa sponsorship as you help reshape the $900B U.S. public education budget.

Qualifications

• Proven experience in AI engineering with a focus on LLM and VLM technologies.
• Ability to work in-person in San Francisco or Phoenix.
• Comfortable with ambiguity and capable of making quick decisions.

Responsibilities

• Build MVPs from scratch for new AI products.
• Optimize accuracy and latency of AI models.
• Create evaluation frameworks for AI behavior.
• Diagnose and fix real-world AI failures.
• Build endpoints and tooling for AI capabilities.

Skills

Experience with LLM APIs

User-centric design

Ability to optimize models

Experience with evaluation frameworks

Job description

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.