Founding Business Ops & Strategy Associate

Posted 19 Hours Ago
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Palo Alto, CA, USA
In-Office
Entry level
Artificial Intelligence • Security • Software
The Role
Own business operations and GTM strategy for an early-stage AI company. Responsibilities include revenue planning, account and segment analysis, commercial funnel diagnosis, pricing and monetization strategy, GTM experimentation, leadership reporting, and cross-functional execution across sales, finance, product, and leadership.
Summary Generated by Built In
Company

Pramaana Labs is a frontier AI lab building the verification layer for AI. Founded in 2025 and headquartered in Palo Alto, we turn complex human knowledge, including tax codes, legal rules, clinical guidelines and security protocols, into formal representations so AI answers can be traced, challenged and proved. Our architecture pairs foundation models trained to formalize and reason with a symbolic world model encoded in Lean 4. Pramaana was founded by a team from Google, DeepMind and Glean, bringing together frontier AI researchers and formal methods experts. Our commercial team is building the go-to-market motion to bring this technology to enterprises where correctness matters most.

The Role

At Pramaana, GTM strategy is still being invented. We are looking for a Business Operations Associate who can turn ambiguous commercial questions into sharp analysis, decisions, and measurable action. You will work closely with our commercial leadership, founders, finance, and product teams to help decide where to play, which customers to pursue, how to price and sell our product, and how to scale what works. This is a strategy-and-execution role, not a reporting function. You might build an account-prioritization model in the morning, listen to an enterprise discovery call in the afternoon, and use both to recommend a better sales motion. The best ideas will be tested in the field, not left in a deck.

What You'll Do
  • Translate ambitious revenue goals into an executable plan: model pipeline coverage, conversion, sales capacity, sales cycles, bookings, ACV and usage-driven expansion; make assumptions and trade-offs explicit.

  • Own strategic account and segment analysis. Develop and continually refine ICPs, vertical priorities, territory hypotheses, account scoring and use-case economics based on actual customer evidence.

  • Diagnose the commercial engine. Combine funnel metrics, win/loss reviews, customer calls and qualitative field feedback to explain what is happening, why, and what to change.

  • Shape pricing and monetization strategy. Evaluate pilots, enterprise contracts, usage-based models, willingness to pay, customer ROI and value capture with Finance and GTM leaders.

  • Run focused GTM experiments on messaging, qualification, outbound, pilots, partnerships and conversion; define a clear success measure before testing.

  • Build the operating cadence for leadership: crisp weekly scorecards, scenario models, pipeline and business reviews, and one-page recommendations with accountable next steps.

  • Partner with RevOps for trustworthy source data and tooling; own the commercial insight, decision support and cross-functional execution that sit above those systems.

You Will Thrive in This Role If You Have
  • Experience in strategy and operations, BizOps, strategic finance, GTM analytics, growth strategy, consulting with operating responsibility, or a high-agency startup role.

  • Exceptional analytical judgment and spreadsheet modeling; ability to go from imperfect raw data to a defensible recommendation and clearly explain assumptions.

  • Commercial curiosity: you want to hear customers, understand buyer incentives and challenge a metric when it contradicts what is happening in the field.

  • Ability to translate strategy into execution across sales, product, finance and leadership without relying on formal authority.

  • Excellent writing and executive communication: concise, structured, willing to take a point of view, and able to revise it when evidence changes.

  • Comfort using modern AI tools and automation to accelerate research, analysis and recurring workflows without sacrificing accuracy.

Especially Strong Candidates May Also Have
  • Built an ICP, territory, sales-capacity, pricing or monetization model that materially changed revenue outcomes.

  • Worked in enterprise AI, developer platforms, cloud, regulated software or a business with both sales-led and product-led growth.

  • Can independently build useful reporting or lightweight internal tools.

Skills Required

  • Experience in strategy and operations, business operations, strategic finance, GTM analytics, growth strategy, consulting with operating responsibility, or a high-agency startup role
  • Exceptional analytical judgment and spreadsheet modeling skills
  • Ability to turn imperfect raw data into defensible recommendations and explain assumptions clearly
  • Commercial curiosity and willingness to engage with customers and challenge metrics
  • Ability to translate strategy into execution across sales, product, finance, and leadership without formal authority
  • Excellent writing and executive communication skills
  • Comfort using modern AI tools and automation to accelerate research, analysis, and workflows
  • Experience building ICP, territory, sales-capacity, pricing, or monetization models that changed revenue outcomes
  • Experience in enterprise AI, developer platforms, cloud, regulated software, or businesses with sales-led and product-led growth
  • Ability to independently build useful reporting or lightweight internal tools
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The Company
HQ: Durham, NC
33 Employees
Year Founded: 2025

What We Do

Pramaana Labs builds the verification layer for AI, translating complex human knowledge—including tax codes, clinical guidelines, legal rules, and safety constraints—into machine-checkable logic. Its domain-specific systems use provers and solvers to search solution spaces and return proof artifacts, counterexamples, and traceable explanations for expert review. The aim is to make AI answers verifiable, challengeable, and defensible, supporting more accountable AI deployment across high-stakes applications.

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