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Lavendo

Founding AI Product Engineer, AI Infrastructure (On-site - San Francisco)

San Francisco

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hirly's read of this role

Role family
Product management
Seniority
Mid level
Stated salary
$200,000 – $250,000 per year
Country
US
Work mode
On-site / unstated
First seen by hirly
9 Sept 2026

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the posting

Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.

About the Company

Our client builds the infrastructure powering how the world's best engineering teams use AI. Their open-source AI Gateway is already trusted by Adobe, Netflix, Nvidia, and NASA — letting developers route 100+ LLM APIs through a single interface with cost tracking, guardrails, load balancing, and logging built in.

They're YC-backed, $14M+ ARR, ~20 people, and just getting started.

The Mission

Make LLM infrastructure simple and scalable for every engineering team on the planet — from scrappy startups to the world's largest enterprises.

The Opportunity

This is a founding-level seat. You'll work directly with the founders to build the company's second major product line from scratch — no inherited codebase to maintain, no backlog of someone else's decisions. You define the shape of what gets built, talk to the customers who'll use it, and ship it yourself. If you want to operate like a founder without the fundraising grind, this is about as close as it gets: real revenue, real customers, real stakes, and a small enough team that your work is immediately visible.

What You'll Do

Talk directly to customers to surface their pain points, pressure-test solutions, and turn raw feedback into shipped features

Build new product features end-to-end, from concept to production, using Python and FastAPI

Partner with the founders to define and build the company's second major product line

Prototype quickly, iterate based on real user feedback, and ship fast in an ambiguous, early-stage environment

Own major product areas spanning backend APIs, the dashboard, and developer experience

What You Bring

2+ years of experience in AI engineering, with a demonstrated ability to ship production code and talk directly to users

A bachelor's degree from a top-25 U.S. CS program

Production Python development experience, with FastAPI preferred, and comfort across backend, frontend, APIs, and infrastructure

Strong hands-on experience with LLM APIs or AI infrastructure (OpenAI, Anthropic, Bedrock, Azure, VertexAI)

A track record of high-intensity, high-ownership work: tenure at a high-growth startup, fast promotions at a top tech firm, or notable entrepreneurial projects in college

Demonstrated initiative signals, such as an active GitHub profile, former startup founder experience, or standout independent projects or competitions

Strong communication skills for direct customer interaction

Key Success Drivers

You own the problem — no one hands you a spec, you write the spec

You talk to users first — building in the abstract isn't your style

You move between worlds — technical depth in the morning, product conversation in the afternoon, same fluency both times

You're built for early-stage — ambiguity is your advantage, not your obstacle

Why Join?

Compensation & Equity

Base salary $200K–$250K

Competitive equity, positioned at the top of the market for seed-stage founding engineers

Traction

  • $14M+ ARR, growing 20% month-over-month, already profitable with no Series A needed
  • Production deployments at NVIDIA, Netflix, NASA, Adobe, AT&T, Okta, and the Department of Defense

40,000+ GitHub stars, with a public changelog and security disclosure practice

Location

On-site in San Francisco, five days a week

Visa Sponsorship Details

Open to visa transfers (OPT, H1B transfers)

Relocation stipend offered for candidates moving within the US

Benefits

Top-tier Medical, Dental, and Vision benefits, including FSA

Join early. Grow fast. Build something that matters

Interviewing Process

Initial screen (15–30 min): overall fit, interest in the role, product intuition, willingness to talk to customers

Technical interview (60 min): production engineering skills, Python proficiency, ability to build and ship across the stack; includes product and system design component

Onsite (4 hours): engineering fundamentals, problem-solving, product thinking, system design, culture fit, and startup mentality

Offer extended

We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.

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Founding AI Product Engineer, AI Infrastructure (On-site - San Francisco) at Lavendo — hirly