Technical Program Manager, Enterprise Commerce

Anthropic's enterprise business is growing fast, and the systems that turn a closed deal into recognized revenue are scaling to keep up. Quote-to-cash spans configure-price-quote, contracting, order management, provisioning, billing, and revenue recognition, and the work to evolve it crosses engineering, GTM systems, finance, legal, and operations teams., * Build and run the cross-team planning and operating cadence for quote-to-cash: a shared roadmap, clear DRIs, sequenced dependencies, and a single source of truth on priorities and status for engineering and finance leadership

• Drive the highest-priority cross-team programs end to end, from scoping and tradeoff decisions through delivery, across engineering, GTM systems, deal desk, order management, accounting, and legal
• Own the SOX readiness program for quote-to-cash systems: gap closure, control design and evidence collection, and coordination with internal audit
• Manage technical dependencies across the stack: CPQ, contract data model, provisioning automation, billing platform, and the integrations between them

• Have 6+ years of technical program management experience, with a track record of building cross-functional programs from scratch in ambiguous environments
• Have technical depth in enterprise systems integration: CPQ, ERP, billing, and provisioning platforms, the data flows between them, and the tradeoffs between configuring SaaS and building custom
• Have run compliance or audit-readiness programs (SOX, SOC, or similar) and understand how control design, evidence collection, and engineering delivery fit together
• Can build trust with engineers, finance and accounting partners, sales operations, legal, and executives, and translate between them
• Thrive when the operating model itself is still being defined and see shaping it as part of the job

Strong candidates may also have

• Background in revenue operations, order-to-cash, billing platform, or finance systems product management
• Familiarity with Salesforce CPQ, contract lifecycle management, or marketplace provisioning (AWS/GCP/Azure), 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.

Pulled from the full job description

• Parental leave
• Flexible schedule, 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.

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 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.