We’re looking for a founding product manager (PM) hire to drive the next phase of company growth through Vals Smith, our enterprise product that tells customers which model is best for their use case.
Every large enterprise organization is now being asked to pick model providers, justify the spend, and defend that choice internally. Almost none of them have evidence. They are making seven- and eight-figure decisions on vibes. Early users have already run Vals Smith against their own repositories, and we have more demand than we have capacity to work.
In this role you’ll own the loop between what enterprise customers need from Vals Smith and what we ship and build the machinery that turns that into repeatable revenue.
What You’ll DoOwn product roadmap for Smith. Run discovery directly with design partners, then ship the changes yourself collaborating directly with engineering + design team: onboarding, repo ingestion, results UX, integrations, demo/POC environments.
Be the technical half of the deal alongside our Head of Partnerships hire. You'll be in the room for evaluations and POCs, own the scoping conversation with a customer's CTO or Head of AI, and turn what buyers push back on into roadmap
Build the activation funnel from signups all the way to recurring use
Play a material role in pricing and packaging. Partner with the founders and GTM on how credits, tiers, and enterprise plans are structured, and own the usage instrumentation and analysis that informs those decisions.
2+ years in a technical, customer-facing role: forward-deployed engineer, solutions engineer, technical PM, ML engineer who's owned customer engagements, or similar.
A technical degree (CS, EE, math) and prior IC engineering experience. You won't be the one shipping our core platform, but you'll write code to scope evals, run experiments with customer data, and build prototypes.
Demonstrated ability to lead a technical engagement end-to-end — from first conversation with a customer's CTO or Head of AI, to scoped statement of work, to delivered eval.
Strong written and verbal communication. You'll be in the room with senior buyers and you need to be credible in 30 seconds.
Ability to work in-person, in San Francisco. We will support your relocation as needed.
Highly competitive salary and meaningful ownership. Excellence is well rewarded.
Relocation and transportation support
Full health, dental, and vision insurance coverage
Lunch and dinner provided, free snacks/coffee/drinks
401K plan
Unlimited PTO
$1,500 housing stipend (within one-mile radius)
Founding team: The core methodology behind this platform comes from NLP evaluation research we had done at Stanford. We work with all the major foundation model labs, some of the largest financial institutions, and hospital systems in the world. Our team has prior work experience at NVIDIA, Meta, Microsoft, Palantir and HRT. Collectively, we have over 300 citations in our published work. Our early team includes Stanford PhDs, ex-Jane Street quants, and the first designer at Snorkel.
We recently announced our $40M Series A at a $400M valuation, led by Andreessen Horowitz, with participation from existing investors 8VC, Pear VC, and Bloomberg and new investors Hudson River Trading and NextLadder Ventures.
Traits We’re Looking For:Learning velocity: The role encompasses a wide variety of tasks. Rather than expecting you to be an expert on Day 1, we are looking for someone who can learn new skills and technologies quickly.
Ownership: Working in a small, talent-dense team, we expect everyone to show initiative to build where it's needed, not where it's asked. We strive for autonomy over consensus.
Intensity: The LLM landscape is constantly changing. Foundation model labs are continuously pushing the frontier. The unicorn companies that will emerge from this technology shift are being built now. Those that win will have an incredibly high speed of execution.
Solution-oriented mindset: We're looking for people who see opportunities to craft solutions at each juncture, not those who pass hard problems to others or admit defeat.
Vals in the Media:
AI tools mostly fumble basic financial tasks, study finds
The Winners (and Losers) of This New Vibe-Coding Benchmark Will Surprise You
OpenAI’s Less-Flashy Rival Might Have a Better Business Model
Meta Announces New AI Model in Major Test of Company’s Ambitions
DeepSeek’s Sequel Set to Extend China’s Reach in Open-Source A.I.
Skills Required
- At least 2 years of experience in a technical, customer-facing role such as forward-deployed engineering, solutions engineering, technical product management, or customer-facing ML engineering
- Technical degree in computer science, electrical engineering, mathematics, or a related field
- Prior individual-contributor engineering experience
- Ability to write code for evaluation scoping, experiments with customer data, and prototypes
- Experience leading technical engagements end-to-end, from customer conversations through statement of work and delivered evaluation
- Strong written and verbal communication skills
- Ability to work in person in San Francisco
What We Do
Vals AI develops independent benchmarks and evaluation systems for leading AI models. It tests models on rigorous, domain-specific real-world tasks spanning finance, law, software, healthcare, coding, and other industries, runs its own evaluations, and creates many benchmarks in-house. Its Vals Index and related reports help organizations compare model performance transparently across specialized tasks and identify the most capable systems for practical use.
