Sales Strategy, Operational Excellence

Own end-to-end delivery of the CCO operating cadence: weekly forecast and pipeline reviews, monthly business reviews, and QBRs

Manage the operational execution behind each review — calendar, prep timelines, templates, and pre-read standards — and hold contributors accountable to deadlines

Prepare the inputs and run the mechanics of each cadence, keeping every session focused on decisions rather than logistics

Capture decisions, commitments, and risks in the room, then assign owners and drive open items to resolution between meetings

Anchor every review in source-of-truth data, ensuring the metrics leadership sees are accurate and consistent from one review to the next

Develop the performance narrative, not just the packet: connect the metrics to what's actually happening in the business and distill what changed, why it changed, and what decision or action it calls for

Build your own view of the forecast — pressure-test bottoms-up calls against pipeline coverage, historical conversion, and deal-level signal, and be willing to say where you'd land differently and why

Spot risk and upside early: identify the deals, segments, or assumptions most likely to move the number, and make sure they get airtime before they become surprises

Establish a single set of KPI definitions, operating standards, and best practices across Sales and Strategy so teams are measuring and running the business the same way

Drive the target-setting process: translate company goals into clear, measurable targets for the field, and keep them current as the business evolves

Document core processes (forecasting methodology, pipeline hygiene, deal stage criteria, rules of engagement) and drive adoption through enablement and reinforcement, not just publication

Design processes that hold up as the organization triples — what works as a spreadsheet today should have a clear path to a system tomorrow — and partner with Systems and Analytics to move repeatable manual work into tooling, using Claude to accelerate documentation, data aggregation, and process design

Experience in sales operations, sales strategy, revenue operations, business operations, or a similar function, with direct experience supporting the operating cadence of a sales organization

Have run or materially supported core GTM planning processes end to end: annual planning, target setting, quota allocation, territory design, or comp plan rollout

Are an exceptional program manager; you can take a loosely defined cross-functional effort, put a plan around it, and drive it to a deadline across teams you don't control

Understand the rhythm of a sales org from the inside: what a forecast call is for, what "commit" means, why pipeline coverage matters, and what makes a quota feel fair or unfair to a rep

Are highly structured and detail-oriented without being rigid; you build the standard, but you know when the standard needs to bend

Communicate clearly and concisely up, down, and across; you can write the one-page pre-read that lets a leadership meeting start at the decision instead of the context

Are fluent in Excel/Sheets (modeling, lookups, structured data) and comfortable working in Salesforce; SQL or Looker experience is a plus but not required

Are energized by bringing order to ambiguity and have a low ego about doing the unglamorous work that makes an organization run

Experience with sales compensation design (SPIFs, accelerators, plan mechanics) and the downstream operational realities of administering them

Exposure to consumption-based or usage-based revenue models where forecasting and quota design don't follow the standard SaaS pattern

Familiarity with planning and territory tools (Anaplan, Pigment, Fullcast, or similar)

A track record of using AI tools to accelerate operational and program management work

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.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.