Director, Finance Systems - Revenue Systems Engineering

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 an experienced Revenue Systems Engineering Director to join our Finance Systems team at Anthropic. You will own the technical architecture, implementation, and optimization of our Order-to-Cash (OTC) systems as we scale globally. You'll serve as the technical lead for our revenue systems within the ERP ecosystem, driving automation of revenue recognition processes and integrating our billing, sales, and financial systems.

Revenue Platform Architecture & Development

• Own the revenue systems architecture and development supporting multi-entity operations and global subsidiaries

• Design and implement scalable data pipelines using DBT/SQL frameworks to transform high-volume financial transactions with low-latency response times for real-time integrations

• Build and maintain automated revenue recognition workflows ensuring ASC 606 compliance for complex subscription and consumption-based billing models

Data Engineering & Pipeline Orchestration

• Modify, enhance, and optimize data transformation models using DBT/SQL to support standardized data flows across accounting, billing engineering, and product teams

• Establish comprehensive testing frameworks for data transformations, formally documenting successful behavior to support System Integration Testing (SIT) and audit requirements

Systems Integration & Technical Leadership

• Collaborate with Revenue Accounting, Data Infrastructure, and BizTech teams to design enterprise-grade integration patterns supporting significant transaction volume growth

• Implement automated reconciliation engines achieving rapid variance detection and substantially reducing manual revenue team effort

• Provide technical expertise during month-end close processes, ensuring system reliability and performance during peak transaction volumes

Innovation & Continuous Improvement

• Pioneer AI integration for revenue operations, building intelligent agents for discrepancy investigation, automated testing, and self-service analytics

• Evaluate and implement emerging technologies to modernize integration architecture

• Establish best practices with CI/CD pipelines, automated testing, and deployment workflows maintaining high reliability standards

• Mentor team members on technical best practices, code reviews, and documentation standards

Minimum qualifications

• Possess strong technical proficiency in Python, SQL, DBT, and modern data engineering tools (workflow orchestration, infrastructure as code, cloud data warehouses)

• Have extensive experience with enterprise billing platforms and revenue recognition requirements (ASC 606)

• Demonstrate expert-level understanding of ERP systems with hands-on configuration and integration experience, including proficiency with API development (REST, SOAP/XML, webhooks) and understanding of ERP extension patterns and custom object development

• Experience with additional programming languages (Java, JavaScript/TypeScript, Go) for building integrations, APIs, and custom ERP extensions

• Track record of leading technical workstreams during ERP transformations or major system migrations

• Are skilled at designing scalable integration architectures, including both real-time APIs and batch processing patterns for high-volume financial transactions

• Have proven ability to translate complex business requirements into robust technical solutions while maintaining alignment with accounting principles and audit standards

• Understanding of consumption-based pricing models, usage metering platforms, and marketplace billing

• Thrive in a fast-paced, high-growth environment where you'll balance innovation with operational stability

• Have excellent communication skills to bridge technical and business stakeholders, including Finance, Accounting, Revenue Operations, and Engineering teams

• Experience implementing revenue platforms at scale for SaaS or subscription-based businesses processing high transaction volumes

• Background in financial systems implementations supporting multi-entity, multi-currency operations with complex revenue recognition scenarios

• Hands-on experience with CRM/CPQ platforms and integration patterns connecting sales systems to billing and ERP systems

• Specific experience with: Salesforce CPQ/Revenue Cloud, Zuora, Stripe Billing,, Workday Financials

• Familiarity with Workday Prism and Oracle Accounting Hub solutions for managing third-party transaction data

• Technical expertise with iPaaS platforms (MuleSoft, Workato, Boomi) and advanced API patterns (GraphQL, event-driven architectures)

• Experience leveraging agentic development workflows

• Experience with AI/LLM integration for financial operations, including document processing, data extraction, and intelligent automation

• Familiarity with Agile/Scrum methodologies and experience working in matrix organizations coordinating across multiple teams

• Knowledge of SOX compliance requirements, financial controls, and audit readiness for revenue systems

• Bachelor's or Master's degree in Computer Science, Information Systems, Engineering, or related technical field

• Hands-on experience with modern data stack tools: Airflow, Terraform, BigQuery/Snowflake/Databricks

• Build and maintain Airflow DAGs orchestrating complex financial workflows, including Python scripts for DBT execution, authenticated API calls, and data quality validation

• Familiarity with financial reporting and business intelligence tools (Hex, Looker, Tableau, Power BI) for revenue analytics and executive dashboards

The annual compensation range for this role is listed below.

$270,000—$315,000 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.