Senior Manager, Finance Systems - Treasury

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 Finance Systems team builds and owns the infrastructure that powers our financial operations and drives the initiatives that scale the Finance function as the company grows. As our financial operations grow in complexity, the team is moving beyond configuring off-the-shelf platforms and into building the production-grade financial applications that no vendor has built for us yet.

• The architecture: design the treasury technology platform and data foundation, make the sequencing and build-vs-buy calls, and get the foundation right so we don't rebuild it in two years.

• The automation: turn Treasury's daily and monthly operating processes (cash positioning, cash flash reporting, forecasting, bank account management, payments) into tested, Claude-powered workflows that a lean team can run.

• The ecosystem: figure out how treasury technology plugs into the broader Finance data lake, the ERP, our banks, and vendor systems, so treasury is a well-governed node in the company's data architecture and ecosystems rather than an island on its own.

You will be the bridge between the Treasury business owners and Finance Systems engineering, turning operational needs into a clear plan and driving it through to production.

This is a foundational leadership role with significant ownership over architecture, vendor, and tooling decisions. You will shape how Anthropic sees and forecasts its cash, with room to grow the team and your scope as the function matures.

Architect the platform

• Define the target-state architecture for treasury technology: the data foundation, the applications that sit on top of it, and how they connect

• Design the treasury data foundation (models, tables, pipelines, governance) as the single source of truth for banking, cash, payments, and investment data

• Lead the treasury management system build-vs-buy evaluation and own the resulting path - vendor selection and implementation, or the internal build

• Sequence the multi-year roadmap so foundational work lands before the capabilities that depend on it, with minimal throwaway work

Automate key treasury processes

• Own the product roadmap for daily cash positioning, cash and liquidity forecasting, cash flash and leadership reporting, bank account management, treasury intake, and payment workflows

• Design and ship Claude-powered agents and dashboards that automate manual, error-prone treasury work, so a lean team can operate at scale

• Partner with Treasury operators to turn their processes into clear product specs, success criteria, and delivery plans, then drive them through to production

• Ensure everything we ship is auditable, controlled, and recoverable, with the rigor that SOX compliance demands as scope grows into controlled processes

Define the ecosystem

• Align treasury data models and governance with the broader Finance data lake strategy so what we build now plugs in rather than gets rebuilt

• Map and own the integration surface across banks, bank connectivity providers, TMS, ERP, and internal finance systems

• Drive the technology agenda with our banking partners, TMS vendors, and connectivity providers tracking their technology roadmaps and partnering on emerging capabilities; partner internally with Accounting, FP&A, Internal Audit, and Data Engineering so treasury systems fit the company's control environment and architecture

• Have 10+ years of experience in product management, technical program management, or systems leadership in finance, treasury, or fintech

• Have deep treasury domain knowledge, including cash positioning, liquidity forecasting, bank connectivity, cash pooling structures , or payment workflows

• Have owned the architecture and platform decisions for an internal finance or data platform across multiple systems and vendors

• Have a track record of shipping internal platforms or finance systems with an engineering team

• Have led complex system design and infrastructure programs, and are comfortable owning architecture and platform decisions across multiple systems and vendors

• Have led a system implementation (TMS, ERP module, or similar) or a material internal build from design through go-live

• Are a strong stakeholder manager across Treasury, Finance, Engineering, Internal Audit (Risk and Compliance)and external vendors

• Communicate clearly in writing and in the room, and can run a steering meeting or land a one-pager with executives

• Thrive in environments where the roadmap, the systems, and the team all need to be built at the same time

• Direct experience with treasury management systems such as Kyriba, Quantum, Trovata, or similar as owner, administrator, or implementer

• Experience integrating with banking APIs, payment rails, or bank connectivity providers

• Experience with cash pooling structures, intercompany funding, or multi-entity treasury operations

• Experience designing or overseeing finance data infrastructure (GCP/BigQuery or a comparable data warehouses, pipelines, reporting platforms) at a program level

• Experience at a high-growth technology company navigating rapid revenue expansion or system consolidation

• Built or product-managed AI/LLM-assisted workflows, agents, or Claude-powered automation for financial operations

• A CTP, CFA, or comparable treasury/finance credential is a nice to have

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.

$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.