Director Order-to-Cash Assurance
Anthropic
Director Order-to-Cash Assurance
Anthropic
Builds Claude AI models with a focus on safety
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's global order-to-cash (O2C) function is scaling faster than the processes and systems behind it, across direct enterprise contracts, consumption-based commercial models, and third-party cloud marketplaces. We're looking for a Director, Order-to-Cash Assurance to make sure every order is priced, billed, collected, and recorded correctly, and that we can prove it.
You'll be embedded in the O2C Transformation team, working closely with Order Management, AR & Collections, Revenue Accounting, Billing Engineering, and Go-to-Market. You'll design and run the pricing audits and accuracy measures that show us where we leak revenue or create rework, then fix the root cause at the source. You'll be the compliance advocate for global O2C, helping the business find the compliant way to yes, and often improving a process by removing steps rather than adding them.
You'll thrive here if you treat accuracy and compliance as design problems and as a service to the business. You are firm when the risk is real, flexible when it isn't, and able to explain the difference. If you're energized by ambiguous, high-consequence operational problems at a company at the forefront of AI development, we'd like to hear from you.
Design and run recurring audit programs across the O2C lifecycle, including pricing audits, contract-to-invoice accuracy, credits, refunds and concessions, and cash application
Define accuracy metrics with baselines and targets, such as pricing and invoice error rates, first-pass yield, rework volume, and revenue leakage, and report them in a way teams can act on
Trace findings to root cause and work with the owning team on the fix, whether in process, system configuration, or contract and pricing standards
Move measurement from periodic sampling to continuous, system-driven monitoring as volume grows
Partner with Order Management and AR operations as their quality partner, and help GTM, Deal Desk, Sales Operations, and Product understand what accurate and compliant looks like through clear published guidance that shortens the path to yes
Review new processes, process changes, commercial models, and exceptions against policy and control requirements, with clear decision rights, service levels, and rationale that stay consistent across regions, entities, and channels
Build compliance into new products, channels, commercial models, and regions by joining at intake rather than at the end
Own O2C policies, control ownership, and segregation of duties
Partner with Internal Audit, external auditors, Revenue Accounting, Tax, and Legal so audit cycles run smoothly, and resolve findings at the root cause
Perform independent review activities, including month-end close reviews, so operations teams can focus on execution while independence is preserved
Create reusable, pre-approved process patterns and guardrails so teams can move quickly without a bespoke review every time, harmonizing globally and localizing only where statute requires
Work with Billing Engineering, GTM Systems, and Business Technology to build controls and accuracy checks into the systems themselves, so quality scales with volume
Deploy AI and automation for exception detection, reconciliation, anomaly detection, and evidence collection
Hands-on experience designing and running audit, quality, or revenue assurance programs within order-to-cash, billing operations, or quote-to-cash
Working knowledge of revenue recognition (ASC 606) and experience partnering with internal and external auditors
Experience with contracting systems, billing platforms, or ERP systems (for example Salesforce, Stripe, or Workday Financials)
Proficiency with SQL or similar tools for analyzing and testing transactional data
Experience using automation or AI for monitoring, testing, or reporting
10+ years of progressive experience in revenue operations, billing operations, revenue assurance, finance operations, or internal controls within order-to-cash at a public company
A track record of simplifying processes, with concrete examples of steps or controls you removed while improving accuracy or strengthening the control environment
A degree in Accounting, Finance, Business, Engineering, or a related field
CPA, CIA, CISA, or CRISC certification, or Lean Six Sigma or PMP certification
Experience building or scaling a SOX program, including readiness for public-company reporting requirements
Experience with global, multi-entity operations, including statutory invoicing and tax considerations
Experience serving both B2C and B2B customers, especially with consumption-based and subscription billing models through to collections
Experience working with go-to-market, deal desk, and revenue operations organizations
Strong cross-functional influence and clear communication about issues and decisions
Understanding of AI industry business models and enterprise customer needs
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.
For roles performing work in California: We will consider for employment all qualified applicants, including those with arrest or conviction records or criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the San Francisco Fair Chance Ordinance, the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act.
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.
Annual Salary: 230000 - 300000 USD
Anthropic builds the Claude family of AI models and sells them to businesses, software developers, and consumers, with research on making AI safe and understandable at the center of its work. In 2024 it introduced the Model Context Protocol, an open standard for connecting AI assistants to outside apps and data that OpenAI and Google adopted the next year. People use the Claude app to write and analyze files, programmers hand coding tasks to Claude Code, and companies build Claude into their own products through its API. Anthropic earns money from subscriptions, business plans, and usage-based API fees. Siblings Dario and Daniela Amodei founded Anthropic in 2021 with other former OpenAI employees, and it is based in San Francisco.
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