Product Finance & Strategy, Monetization

Anthropic
San Francisco, US
Visa sponsorship

Who this role is best for

Best suited to mid-level finance professionals with AI industry passion and experience in monetization strategy, operating in a high-autonomy role with 25% office presence in San Francisco.

Best fit for

  • Finance professionals with a passion for AI economics and strategic decision-making.
    — “passionate about applying financial rigor to the economics of frontier AI
  • Candidates with experience in high-autonomy roles requiring independent decision-making.
    — “high-ownership, high-autonomy role for someone who genuinely loves to model
  • Individuals with a strong background in financial modeling and analysis.
    — “Advanced proficiency in spreadsheet-based financial modeling

Things to consider

  • Requires 25% office presence in San Francisco, limiting full remote flexibility.
    — “expect all staff to be in one of our offices at least 25% of the time
  • Visa sponsorship is not guaranteed for all candidates.
    — “we aren't able to successfully sponsor visas for every role

How to stand out

  • Demonstrate a deep understanding of AI token economics and compute costs.
    — “connect token economics, inference and compute costs, and margin to pricing
  • Highlight specific examples of pricing strategy or monetization projects.
    — “Direct experience owning pricing, packaging, or monetization strategy
  • Showcase cross-functional collaboration with product and go-to-market teams.
    — “Partner cross-functionally with product, go-to-market, and compute stakeholders
Pace · Fast PacedCollaboration · HighAutonomy · HighDecision Impact · TeamLevel · Mid Level

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • model monetization end to end
  • build business cases for enterprise and vertical product investments
Typical background
investment bankingprivate equitymanagement consulting

Skills & requirements

Required

Financial ModelingInvestment BankingPrivate EquityManagement ConsultingSpreadsheet Proficiency

Preferred

AI MonetizationEnterprise And Vertical Product Investments

About the role

Original posting from Anthropic via Greenhouse

About Anthropic

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.

About the role

We are seeking a Finance & Strategy team member to drive two of the most consequential financial workstreams at Anthropic: Model Monetization and Enterprise & Verticals. On one side, you'll own the economics behind how we price and package — spanning list pricing, tiering, and consumption mechanics across our model families. On the other, you'll serve as the Finance & Strategy partner to our Enterprise and Verticals product teams — shaping the business cases, product economics, and investment decisions behind what we build for enterprises and priority industries. Together, these determine how the business world accesses frontier AI..

This is a high-ownership, high-autonomy role for someone who genuinely loves to model and is energized by hard, ambiguous questions. You'll connect token economics, inference and compute costs, and margin to pricing and packaging decisions, and bring that same rigor to enterprise and vertical product investments. We're looking for someone opinionated and decisive, you'll be expected to form a view, defend it with rigorous analysis, and drive it to a decision. A deep, current obsession with AI and a perspective on where the field is heading will make you far more effective here.

If you are passionate about applying financial rigor to the economics of frontier AI, join us in making AI safe and impactful.

Key responsibilities

Own model monetization end to end: build and maintain the financial models that connect token economics, inference and compute costs, and margin to pricing and packaging decisions across our model family and API

Serve as the Finance & Strategy partner to our Enterprise and Verticals product teams, owning the financial lens on what we build for enterprises and priority industries

Build the business cases behind enterprise and vertical product investments: size opportunities, model product economics and pricing, and evaluate the return on competing roadmap bets

Partner cross-functionally with product, go-to-market, and compute stakeholders to evaluate pricing and packaging changes, new model launches, and consumption-based offerings, translating analysis into clear, opinionated recommendations

Analyze the drivers of unit economics and gross margin, surfacing the trends, risks, and opportunities that should inform monetization and product strategy

Track the competitive and market landscape for AI monetization and enterprise adoption, bringing an outside-in view that sharpens our own strategy

Form and defend a point of view on monetization and product investment decisions, delivering clear, concise analyses that drive to resolution with executives and cross-functional partners

Collaborate with finance, FP&A, and accounting counterparts to ensure decisions are consistent with broader financial strategy and reporting

Establish and maintain reporting dashboards that track key pricing, margin, consumption, and product performance metrics

Minimum qualifications

A background in investment banking, private equity, management consulting, or a comparable analytically rigorous role

Advanced proficiency in spreadsheet-based financial modeling, with the ability to build and maintain complex operating models from the ground up — and genuine enjoyment of the craft

Demonstrated ability to take full ownership of a workstream and drive it independently from question to decision

The judgment and conviction to form an opinion and defend it, paired with the openness to update it as the analysis evolves

A genuine, current obsession with AI — you follow the field closely and have a perspective on where it is going

Ability to communicate complex financial information clearly to non-finance audiences

Passion for Anthropic's mission to build safe, transformative AI systems

Preferred qualifications

Experience across investment banking, private equity, growth equity, venture capital, management consulting, strategic finance, or product finance

Operating experience inside a company, not solely in an advisory or investing seat

Direct experience owning pricing, packaging, or monetization strategy — for example, setting or revising list prices, designing tiering and packaging, running pricing research, or measuring the impact of pricing changes

Experience partnering with a product organization on business cases, investment decisions, or roadmap prioritization

Experience with usage-based, API, or developer platform pricing, or other consumption-based business models

Knowledge of and interest in cloud computing infrastructure and compute economics

Proficiency in SQL

The annual compensation range for this role is listed below. 

For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.

Annual Salary:$240,000—$325,000 USDLogistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.

How we're different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given t

Source: Anthropic careers (Greenhouse)

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