About the role

As a Product Manager, Technical, you will own and be responsible for building a world class support experience for Anthropic's customers and the Product Support team. You will partner with Product Support Operations, AI Support, Billing, Fraud, and Product Engineering teams to build the systems that decide how Anthropic's users get unblocked when something goes wrong, and how what they report turns into product fixes, in partnership with the product teams that own the experience. Claude will be the primary operator of that support experience.

• Partner with Product Support Operations, AI Support, and product engineering teams to own the systems behind the support experience end to end: the path from a recurring support driver to a shipped product fix, the Claude-based AI support layer that handles most inbound volume, and the tooling that helps human agents resolve what’s left quickly and accurately. .
• Your north star is fewer support cases per user, and whole categories of cases eliminated, even as the product grows. The best outcome is a case that never gets opened because the product problem behind it was found and fixed. Everything in the support experience is in scope. You decide where to start.
• You'll define the end-to-end experience Claude delivers: diagnosing a billing failure, resolving it or escalating it, recognizing when the same failure is showing up across many customers, filing the bug with repro steps and a proposed fix, getting that to the engineering team that owns the driver, following up with the customer to confirm the issue was actually resolved, and confirming the category actually goes away once the fix ships.
• You will define and own the strategy and roadmap for the support-to-product feedback loop, including the escalation paths for billing, fraud, and high-visibility cases, and the metrics that show whether contact rate is falling.

Responsibilities

• Deeply understand the needs of Product Support Operations, AI Support, Billing, Fraud, and the product engineering teams that own support drivers, from specialists handling enterprise escalations to engineers who need a support case turned into a reproducible bug they can fix.
• Define and iterate on the support-to-product loop: how a case is classified, how recurring drivers are surfaced in near real time with case examples and recommended fixes, how each driver gets a named owner, and how we confirm the fix decreased case volume. Own the metrics behind it: inbound case volume by driver, drivers fixed at the root, and time from first case to shipped fix, alongside the response-time and CSAT targets Product Support Operations already runs on.
• Own the customer's experience of getting unblocked: how quickly a user reaches a resolution and how little friction they hit on the way, whether Claude resolves the case or hands it to a specialist.
• Minimize the blast radius of novel issues. New models and product changes will keep creating new drivers no one can predict; catch each one at its first reports, assess impact, and get the fix prioritized while the affected group is still small.
• Partner with engineering and data science to build the systems that scale with Anthropic’s growth: Claude as the first responder, the data pipeline behind driver detection, and the tooling that lets Claude hand a diagnosed case to the right team.
• Drive product strategy and roadmap for the in-house Claude support layer, including what Claude resolves on its own, what it escalates and to whom, and how far it goes toward filing and fixing the underlying product issue itself.
• Own the trade-off framework between intake reduction, response time, cost, and quality, making transparent prioritization decisions about which drivers get fixed first and communicating them clearly to Product Support and senior leadership.
• Build conviction about what support looks like when Claude is the primary operator, and translate that into a roadmap that gets Anthropic there ahead of the volume curve.

You may be a good fit if you have

• 7+ years of product management experience, with deep exposure to support systems, customer operations tooling, billing or payments, or internal platforms that serve 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 the needs of multiple personas, and of making prioritization trade-offs between them and communicating them clearly
• Ability to internalize complex technical systems (case routing, billing and payments flows, LLM-based agents, data pipelines) and translate that understanding into a comprehensive product vision
• Fluent across functions: you're equally credible reading a failed-payment trace with engineers, walking a specialist through why a driver got deprioritized, and explaining intake trends to leadership
• A strong thesis on how AI changes support: you've thought deeply about what happens when the agent that answers the case can also diagnose, file, and fix what caused it, and you want to build that
• Experience scaling an LLM-based product or experience from prototype to real volume, and a clear view of what breaks on the way: quality drift, cost, latency, and user trust
• Scrappy and resourceful: you do what it takes to get things done in a fast-moving environment

Strong candidates may have:

• Built or scaled the systems behind a high-volume support operation for consumer or developer products: case data pipelines, driver analytics, or LLM-based support agents.
• Shipped an LLM-based support or operations agent in production and understand the trust, escalation, and quality-measurement problems that come with it.
• Defined and operationalized contact-rate or case-deflection metrics, and a point of view on how those metrics change when the fix ships in the product instead of the help center.
• Scaled through hypergrowth in support-heavy environments (consumer subscriptions, developer platforms, or fintech).
• Experience getting product and engineering teams to own support drivers, with proven evidence of driving ownership through clear evidence and product quality.