Founding Head of Partnerships (Vals Smith)

Posted 15 Hours Ago
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San Francisco, CA, USA
In-Office
150K-200K Annually
Mid level
Artificial Intelligence • Machine Learning • Software • Analytics
The Role
Own the full enterprise sales cycle for Vals Smith, including outbound prospecting, discovery, technical evaluations, negotiations, closing, and expansion. Build the go-to-market playbook, define the ideal customer profile, develop qualification and outbound processes, and optimize packaging and objection handling. Partner with founders, product, and engineering teams on evaluations and POCs while translating complex AI technology into business value for enterprise decision-makers.
Summary Generated by Built In
About the Role

We’re looking for a founding Head of Partnerships 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 be responsible for generating pipeline, running complex enterprise sales cycles, and building the go to market playbook for Vals Smith from the ground up.

What You’ll Do
  • Own the full sales cycle for Vals Smith — outbound, discovery, technical evaluation, negotiation, close, and expansion. Interact with senior leaders and decision makers at large enterprises

  • Work three pipeline sources from day one: inbound from our launch waitlist and early users, warm introductions from our founders and investors, and cold outbound you generate yourself

  • Build the playbook, including ICP definition, qualification criteria, outbound sequences, packaging, and objection handling

  • Work side by side with our founding PM and engineering team. You'll run technical evaluations and POCs together, carry what you hear in deals back into the roadmap and how we package the product

  • Use data and tooling to continuously monitor impact metrics and optimize strategy

What We're Looking For
  • 3+ years of enterprise sales experience in SaaS or technology, ideally with exposure to AI. Proven success closing six‑figure deals and managing complex sales cycles with multiple stakeholders.

  • Relevant and recent experience in outbound prospecting, especially to technical and enterprise personas

  • You do not need to write code but should have experience selling technical solutions to product and engineering leaders and the ability to translate complex technology into business value.

  • Comfort operating in an early-stage, high-growth environment, building new motions from scratch and iterating quickly.

  • Ability to work in-person, in San Francisco. We will support your relocation as needed.

What We Offer:
  • 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)

About Us:

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.

What 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

  • 3+ years of enterprise sales experience in SaaS or technology
  • Proven success closing six-figure deals
  • Experience managing complex sales cycles with multiple stakeholders
  • Recent experience in outbound prospecting to technical and enterprise personas
  • Experience selling technical solutions to product and engineering leaders
  • Ability to translate complex technology into business value
  • Ability to work in person in San Francisco
  • Exposure to AI
  • Comfort operating in an early-stage, high-growth environment
  • Ability to build new sales motions from scratch and iterate quickly
Am I A Good Fit?
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The Company
12 Employees
Year Founded: 2023

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.

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