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Salary: USD 385,000 - 460,000 / annual
Anthropic is seeking a Technical Product Manager to own and build a world-class support experience for customers and the Product Support team. This role sits at the intersection of product, operations, and engineering, responsible for the end-to-end systems that move customers from support cases to shipped product fixes.
You will partner with Product Support Operations, AI Support, Billing, Fraud, and Product Engineering teams to design and scale the support experience. Your north star is reducing support cases per user and eliminating entire categories of issues as the product grows. The best outcome is a case that never opens because the underlying product problem was found and fixed.
Key responsibilities include:
- Defining the end-to-end experience Claude (Anthropic's AI) delivers in support: diagnosing issues, resolving or escalating them, recognizing patterns across customers, filing bugs with repro steps, and confirming fixes resolve the category.
- Owning the support-to-product feedback loop strategy and roadmap, including escalation paths for billing, fraud, and high-visibility cases, and metrics showing whether contact rate is falling.
- Understanding the needs of multiple teams—from enterprise specialists to engineers—and translating those into a comprehensive product vision.
- Defining and iterating on how cases are classified, how recurring drivers are surfaced in near real-time with examples and recommended fixes, and how to confirm fixes decrease case volume.
- Owning customer experience: how quickly users reach resolution and how little friction they encounter, whether Claude resolves the case or escalates to a specialist.
- Catching novel issues early, assessing impact, and getting fixes prioritized while the affected group is small.
- Partnering with engineering and data science to build systems that scale: Claude as first responder, data pipelines for driver detection, and tooling for case routing.
- Driving product strategy for the Claude support layer, including what Claude resolves independently, what it escalates, and how far it goes toward filing and fixing underlying product issues.
- Owning trade-off frameworks between intake reduction, response time, cost, and quality, making transparent prioritization decisions and communicating them to Product Support and leadership.
- Building conviction about what support looks like when Claude is the primary operator and translating that into a roadmap that scales ahead of volume growth.
Requirements:
- 7+ years of product management experience with deep exposure to support systems, customer operations tooling, billing/payments, or internal platforms serving operations teams.
- Experience taking technical platform products from infancy to scale; you've built something from the ground up and grown it to serve demanding internal or external engineering customers.
- Track record of building products that balance multiple personas' needs and making clear prioritization trade-offs.
- Ability to internalize complex technical systems (case routing, billing flows, LLM-based agents, data pipelines) and translate understanding into comprehensive product vision.
- Fluency across functions: credible reading failed-payment traces with engineers, explaining driver deprioritization to specialists, and presenting intake trends to leadership.
- Strong thesis on how AI changes support; deep thinking about what happens when the agent answering the case can also diagnose, file, and fix the underlying issue.
- Experience scaling an LLM-based product from prototype to real volume, with clear understanding of what breaks: quality drift, cost, latency, user trust.
- Scrappy and resourceful; ability to execute in fast-moving environments.
Strong candidates may also have:
- Built or scaled systems behind high-volume support operations for consumer or developer products (case data pipelines, driver analytics, LLM-based support agents).
- Shipped an LLM-based support or operations agent in production and understand trust, escalation, and quality-measurement challenges.
- Defined and operationalized contact-rate or case-deflection metrics with a point of view on how those metrics change when fixes ship in the product.
- Scaled through hypergrowth in support-heavy environments (consumer subscriptions, developer platforms, fintech).
- Experience getting product and engineering teams to own support drivers with proven evidence of driving ownership.
