Product Operations Manager, Feedback Loops
About the role
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.
About Anthropic
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.
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.
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.
Qualifications
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.
Be 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.
Be service-oriented and obsessed with making it easy for others to do great work.
Preferred Qualifications
Experience with building AI-native workflows end-to-end — prompt design, evals, closed-loop improvement — and pushing the boundaries of what automation can own.
Experience with Product Management, Customer Success Operations, or Research Operations.
Experience with Feedback tooling ecosystems (Productboard, Dovetail, or homegrown equivalents) and the tradeoffs between buy vs. build.
Treatment of process as a product with users, metrics, and continuous iteration.
Track record of building and scaling operations programs from zero to one.
Compensation
The annual compensation range for this role is $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
We currently 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.
How we're different
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.
Our Mission
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.