Finance & Strategy, Compute

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.

We are seeking a Strategic Finance Lead to provide finance leadership for our accelerator investments. In this role, you will be a key partner to our compute teams, providing financial expertise and guidance to optimize our compute investments and drive strategic decision-making.

In this role, you’ll develop deep expertise in the economics of AI compute, from the unit economics of individual training runs to the long-range financial planning of our accelerator fleet. You’ll build financial models that inform Anthropic’s investment decisions, own planning and forecasting processes for major cost centers, and translate complex technical dynamics into clear financial narratives for leadership.

This is a high-impact role for someone who thrives at the intersection of finance and technology, and who is energized by building frameworks from scratch in a fast-moving environment.

Key responsibilities

• Finance lead for cloud accelerator compute spend, including budgeting, monthly forecasting, variance analysis, and financial plan maintenance
• Build and maintain detailed bottoms-up data-driven financial models for accelerator infrastructure, including long-range forecasts, cost driver analyses, and investment scenario modeling
• Develop deep expertise in compute contracts, pricing structures, and cost drivers, and surface optimization opportunities across our infrastructure
• Serve as subject matter expert for Anthropic’s overall compute capacity plan, owning source of truth and plan of record
• Support the implementation and management of financial planning tools (e.g., Pigment), ensuring our models and processes scale with the organization
• Analyze the economics of model training and research compute, including ROI across different dimensions like training run sizes, chip types, data, etc, and distill into actionable framework for capacity planning and deployment
• Partner closely with engineering and research teams to understand how training and reinforcement learning processes scale, and translate those technical dynamics into financial frameworks

• Exceptional analytical skills with an ability to synthesize data into compelling insights and develop complex financial operating models
• Extraordinary problem-solving and critical thinking abilities to come up with new frameworks for assessing profitability and capital efficiency in a rapidly evolving industry
• Attention to detail and patience for getting to the source of truth on complex and interconnected underlying financial and legal frameworks
• Comfort working cross-functionally and are adept at communicating complex financial information to non-finance audiences

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.

• 7+ years of experience in strategic finance, infrastructure investment, private equity, growth equity, consulting, or investment banking, preferably with infrastructure, datacenter, or technology infrastructure experience
• 3+ years of experience specifically in cloud infrastructure financial management
• Experience working directly with major cloud service providers (AWS, GCP, Azure)
• MBA or other advanced degree in finance, economics, or business

$190,000—$240,000 USD

Logistics

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 time. As such, we greatly value communication skills.