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.
Anthropic exists to ensure the world safely navigates the transition through transformative AI. That work is funded by commercial revenue — and that revenue runs through Billing Platform. The Product Monetization team builds the on-rails that let every product team at Anthropic — Claude.ai, the Developer Platform, Claude Code — monetize features and convert users into paying customers without becoming billing experts themselves. The faster product teams can ship and charge, the faster Anthropic can fund the mission.
We're looking for an Engineering Manager to lead this team. You'll own the platform layer where product meets revenue: the integration contracts product teams plug into, the constructs that let the business run pricing experiments, the self-serve and promotional capabilities Growth builds on, and the payment methods that open up global markets. You'll partner closely with Growth, Safeguards, Legal, and the core Billing Infrastructure team, and work tightly with Customer Support to continuously improve the billing experience for customers.
Lead and grow a team of engineers building the revenue-enablement platform — hiring, coaching, and setting a high technical bar.
Build the on-rails: clean billing API abstractions and integration contracts so product teams can onboard and launch paid SKUs seamlessly, without billing logic leaking into their stack.
Define and own the platform's reliability bar — tiered SLOs and SLAs organized by customer impact: error budgets on the "can the customer do the thing" flows, quality targets on everything else.
Build the platform constructs that let the business run pricing experiments and iterate on monetization models with real data.
Partner closely with Growth — own the promotional, trial, and self-serve billing platform they build campaigns on top of. Your team owns the platform; Growth owns the campaigns.
Expand payment method coverage globally, driving up authorization rates and conversion in markets where default card flows underperform.
Ship new monetization models that keep pace with how the product portfolio evolves.
Drive down time-to-market for new SKUs and product launches — the team's core input is "product team needs to charge for X," and your job is to make that fast.
Have 3+ years of engineering management experience, with 8+ years total in the industry.
Have led teams building payments, billing, subscription, or monetization systems — and know firsthand how a small pricing change ripples through the whole stack.
Have strong opinions about platform boundaries and API design.
Are good at cross-functional work — Growth, Legal, Customer Support, Safeguards, and product teams will all have opinions and you need to keep them aligned.
Direct experience with modern billing and payment platforms — and opinions on when to build vs. buy.
Built or scaled local payment method adoption for international markets.
Run a promotional/offers platform that fed directly into growth or subscription conversion funnels.
Experience in a PLG or self-serve SaaS environment where billing UX is a conversion lever, not an afterthought.
Managed teams through regulatory or compliance-heavy work (consumer financial terms, tax, etc.).
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.
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.
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.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.