Finance Systems Engineer, Tax

Anthropics 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.

Anthropics Tax Technology function sits inside Finance Systems and owns the systems that make every revenue and purchasing motion bookable taxable and auditable from day one. Were looking for a tax technologist who builds: someone who already understands how tax systems work and who writes the integrations tooling and production code that connect them to Anthropic billing ERP and data warehouse systems.

Youll build across all of tax including indirect tax corporate income tax and provision withholding tax R&D credits and transfer pricing. Youll be a foundational hire on a small team working directly with the Tax Technology Lead and be a trusted partner to our cross functional partners in Tax Data Science Billing Engineering and Product among others. Youll be the key Anthropic tax technology technical resource building and hardening the tax-specific tooling and audit-ready evidence pipelines that allow the function to keep pace as the business grows.

This role is expected to take on more ambitious projects over time including using Claude to automate tax work end to end and building internal products that are both high impact and seamless to use for the Tax team.

• Own tax-related changes in the billing codebase and the billing-to-tax-engine integration including withholding tax considerations
• Lead the AP tax engine implementation across ERP-connected purchasing flows: data migration integration pipelines parallel-run reconciliation e-invoicing and go-live validation
• Build and iterate tax-specific products and internal tooling across the full tax stack including indirect tax reconciliations provision and research credit data pipelines transfer pricing datasets withholding tracking and exemption and validation tooling
• Own the production connection points between the tax stack and our data infrastructure feeding the central ingestion layer
• Build SOX-aware IPE and control-total tooling on tax data flows: ingestion control totals source-to-target tie-outs and evidence pipelines that stand up to external audit
• Design and build tooling that applies Claude to tax work and gives non-technical tax colleagues self-serve access to data calculations and evidence
• Serve as the technical owner for vendor implementation handoffs in the room during the build and accountable after go-live
• Partner with Billing Engineering Data Platform Tax Treasury and Product to keep the tax stack optimized and compliant as new products and jurisdictions come online

• Hands-on experience building or owning production integrations against billing platforms ERPs or enterprise tax or finance systems
• Tax-systems fluency in at least one domain (indirect tax engines corporate tax provision or compliance tooling withholding research credit or transfer pricing systems) gained at a tax-technology practice a tax software vendor or an in-house tax-systems team
• Proficiency writing production-grade Python with testing and code-review discipline
• SQL proficiency sufficient to build reconciliations and validate data end to end
• Experience building or operating SOX-aware data flows such as IPE control totals or documented and testable pipelines
• Ability to work independently in a constantly changing and fast paced environment
• Ability to work directly with vendors auditors engineers and the tax team without an intermediary

• 7 years in tax technology finance systems engineering or a closely related field
• Experience owning changes inside a shared production codebase alongside a product engineering team
• Warehouse and analytics-engineering skills such as dbt BigQuery or comparable
• Breadth across multiple tax domains including indirect (sales/use VAT/GST) corporate income tax and provision withholding research credit and transfer pricing data
• Experience building internal tools or interfaces for non-technical finance or tax users
• Experience building with LLMs or applying AI to finance or tax work
• Marketplace usage-based or platform billing exposure
• Experience taking over vendor-built systems and hardening them for long-term ownership
• UAT design and change-management experience on finance-systems implementations
• Record of novel AI applications for foundational tax tasks or problems

Minimum education: Bachelors 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 arent 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 youre interested in this work. We think AI systems like the ones were 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.

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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. Were 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 aboutour policy for using AI in our application process.