Product Manager (Technical), Product Support Experience

Anthropic•San Francisco, NY

11h•Hybrid

About The Position

Anthropic is hiring a Product Manager, Technical, to build and own a world-class support experience for customers and the Product Support team. The role partners with Product Support Operations, AI Support, Billing, Fraud, and Product Engineering to develop the systems that unblock users and turn reported issues into product fixes. Claude will be the primary operator of the support experience, with the goal of reducing support cases per user and eliminating recurring categories of cases as the product grows. The Product Manager will own the end-to-end support-to-product feedback loop, from classifying cases and identifying recurring drivers to assigning engineering owners, shipping fixes, and verifying that case volume falls. The role also defines the experience Claude provides, including resolving or escalating cases, identifying widespread issues, producing actionable bug reports, and following up with customers. It owns strategy and roadmaps for the Claude support layer, support tooling, escalation paths, and the metrics used to measure customer outcomes and operational performance. This position requires aligning the needs of customers, support specialists, engineers, and leadership; balancing intake reduction, response time, cost, and quality; and scaling the systems as Anthropic grows. The role is based under Anthropic’s hybrid policy, which currently expects staff to work from an office at least 25% of the time, though some roles may require more office time.

Requirements

At least 7 years of product management experience, with deep exposure to support systems, customer operations tooling, billing or payments, or internal platforms serving operations teams.
Experience taking technical platform products from infancy to scale, including building for demanding internal or external engineering customers.
Track record of building products for multiple personas, making prioritization trade-offs, and communicating decisions clearly.
Ability to understand complex technical systems—including case routing, billing and payments flows, LLM-based agents, and data pipelines—and translate that understanding into a comprehensive product vision.
Ability to work credibly across functions, including discussing technical traces with engineers, explaining prioritization to specialists, and presenting intake trends to leadership.
A strong point of view on how AI changes support, including the potential for an agent to diagnose, file, and fix the causes of customer cases.
Experience scaling an LLM-based product or experience from prototype to real volume, with an understanding of quality drift, cost, latency, and user trust.
Resourcefulness and ability to deliver in a fast-moving environment.
Bachelor’s degree or an equivalent combination of education, training, and/or experience.
A field of study relevant to the role, demonstrated through coursework, training, or professional experience.

Nice To Haves

Built or scaled systems behind a high-volume support operation for consumer or developer products, such as case data pipelines, driver analytics, or LLM-based support agents.
Shipped an LLM-based support or operations agent in production and understand its 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 a product fix replaces a help-center solution.
Experience scaling through hypergrowth in support-heavy environments such as consumer subscriptions, developer platforms, or fintech.
Experience getting product and engineering teams to own support drivers, with evidence of driving ownership through clear evidence and product quality.

Responsibilities

Understand the needs of Product Support Operations, AI Support, Billing, Fraud, and product engineering teams, including specialists handling escalations and engineers responsible for support-related product issues.
Define and iterate on the support-to-product feedback loop, including case classification, near-real-time identification of recurring drivers, examples and recommended fixes, named ownership for each driver, and confirmation that fixes reduce case volume.
Own support metrics, including inbound case volume by driver, root-cause fixes, time from first case to shipped fix, and existing response-time and CSAT targets.
Own the customer experience of getting unblocked, including resolution speed and friction whether Claude resolves the case or escalates it to a specialist.
Detect novel issues early, assess their impact, and get fixes prioritized while the affected customer group is small.
Partner with engineering and data science to build scalable systems, including Claude as first responder, the driver-detection data pipeline, and tooling to route diagnosed cases to the appropriate team.
Drive strategy and roadmap for the in-house Claude support layer, including what Claude resolves or escalates, escalation recipients, and its role in filing or fixing underlying product issues.
Own the trade-off framework for intake reduction, response time, cost, and quality; make prioritization decisions and communicate them to Product Support and senior leadership.
Develop and communicate a vision and roadmap for Claude as the primary operator of support, ahead of projected support volume growth.