Product Operations Manager, Feedback Loops

Anthropic$260K — $325K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 7+ years in product operations or customer insights and voice of the customer programs at tech companies.
  • Experience shipping AI-enabled processes and systems, including hands-on with LLM workflows.
  • Proven experience managing end-to-end customer feedback programs that inform product decisions.
  • Background in fast-paced environments, ideally Series B-D companies, developing initial versions of products quickly.
  • Strong ability to build shared infrastructure across multiple teams and influence adoption without direct authority.

Responsibilities

  • Own the organization-wide customer feedback operating system across all teams.
  • Capture and structure customer feedback from diverse channels into a single system of record.
  • Build streamlined intake workflows that minimize documentation burden for teams.
  • Create AI-powered systems for effective feedback synthesis and triage.
  • Ensure feedback is routed efficiently to the appropriate product or research teams.
  • Design and run structured voice of the customer programs for deeper insights.
  • Track and improve metrics related to feedback loop efficiency and impact.

Benefits

  • Hybrid work policy allowing flexibility with office presence.
  • Visa sponsorship assistance for eligible candidates.
  • Opportunities for continuous learning and skill development.
Full Job Description
We're hiring a Product Operations Manager - Feedback Loops to own and continuously improve how customer signal flows into product and research decisions at Anthropic. This is a horizontal, org-wide role - you won't be embedded in a single product team, you'll build the shared operating system for voice of the customer that every product team, every surface, and every GTM motion plugs into. Feedback at Anthropic is uniquely high-leverage. We're building on frontier models that evolve constantly, serving customers from individual developers to the largest enterprises, across multiple surfaces (API, claude.ai, Claude Code). Customer signal arrives from everywhere - field conversations, support interactions, early access programs, in-product telemetry - and the opportunity is to make that signal a first-class, structured input to every product and research decision. This role will build the system that makes customer voice as easy to act on as any other data source. You treat feedback loops as a product. You're obsessed with making it effortless for the field to share what they're hearing and for product teams to know what matters most. You build AI-enabled systems that do the first pass so humans can focus on judgment, not triage. You think like a product manager, not a process administrator. Your work will directly impact how fast Anthropic learns from its customers and how reliably that learning shapes what we build next. Key Responsibilities You'll own the operating system for customer feedback across all of Anthropic - one shared platform, not a collection of per-team processes. Working horizontally across every Product team, Research PM, GTM, Customer Success, and Support, you'll establish the intake, synthesis, and routing infrastructure that makes voice of the customer a first-class input to every roadmap. You'll drive adoption through influence, making it so obviously useful that teams pull from it rather than get pushed to it. Feedback Intake & System of Record - Own the single, org-wide pipeline that captures customer feedback from every channel - field teams, support, early access programs, in-product signals - into one structured system of record that serves every product surface. - Build intake workflows that meet teams where they already work (Slack, Gong, CRM) without creating a documentation tax. Obsess over the submitter experience so that sharing feedback is faster than not sharing it. AI-Enabled Synthesis & Triage - Build Claude-powered pipelines that enrich, tag, cluster, and summarize unstructured feedback into trackable issues - doing the first-pass work so humans focus on verification and judgment. - Design the human-in-the-loop model: Claude proposes, PMs and field teams correct, and the system learns from those corrections over time. - Partner with Engineering and Research on tooling strategy, evals, and the closed-loop data that makes synthesis quality measurably improve. Routing & Closing the Loop - Establish clear routing so the right feedback reaches the right product or research owner at the right time - including the path from product signal back into model training priorities. - Build the visibility layer that gives GTM and Support a clear line of sight from customer input to roadmap outcome, so they can close the loop with customers confidently and in real time. Voice of the Customer Programs - Partner deeply with GTM, Customer Success, and Sales to design and run structured voice of the customer programs - customer advisory boards, early access programs, design partner cohorts - that generate high-signal feedback by design. - Define what "high-signal" means: feedback tied to specific use cases, blocker severity, revenue context, and customer segments so product teams can make confident tradeoffs. Continuous Improvement - Define and track success metrics for feedback loop health - time-to-triage, signal quality, roadmap influence, field satisfaction - and use them to identify bottlenecks. - Run regular retros with Product and GTM partners and feed learnings back into process and tooling improvements. Scale what works through documentation and enablement. You may be a good fit if you: - Have 7+ years in product operations, customer insights, voice of the customer programs, or related roles in fast-paced tech companies. - Have personally shipped AI-enabled processes and systems - you've written the prompts, built the evals, and iterated on production LLM workflows yourself. You can talk about model behavior with specificity, not just direct others to build. - Have owned a customer feedback program end-to-end - intake, synthesis, routing, and closing the loop - that product teams actually used to make decisions. The customer mix can be enterprise, PLG, design partner, or dev community; what matters is that you designed it and ran it. - Have operated at earlier-stage and scaling companies (Series B-D or equivalent) where you built things that didn't exist yet, shipped v1s in weeks not quarters, and iterated in public. - Have operated in horizontal, cross-org roles before - you know how to build shared infrastructure that many teams depend on, drive adoption through influence rather than mandate, and earn trust across functions that don't report to you. - Are comfortable with ambiguity and can create structure where none exists - you've built the v1 of a system and iterated it into something teams rely on. - Are service-oriented and obsessed with making it easy for others to do great work. Strong candidates may also have experience with: - Building AI-native workflows end-to-end - prompt design, evals, closed-loop improvement - and pushing the boundaries of what automation can own. - Product Management, Customer Success Operations, or Research Operations. - Feedback tooling ecosystems (Productboard, Dovetail, or homegrown equivalents) and the tradeoffs between buy vs. build. - Treating process as a product with users, metrics, and continuous iteration. - Track record of building and scaling operations programs from zero to one. 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. Annual Salary: $260,000-$325,000 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.

About Anthropic

Anthropic is an artificial intelligence research lab that focuses on developing AI systems that are safe, reliable, and trustworthy. The company was founded in 2019 by Dr. Yoshua Bengio, a leading AI researcher and winner of the Turing Award. Anthropic's research is focused on developing AI systems that can learn from small amounts of data, reason about complex systems, and interact with humans in a natural way. The company is based in New York City and has a team of experienced AI researchers and engineers.
Learn more about Anthropic
Size
50 employees
Industry
Founded
2019

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