Product Operations Manager, Feedback Loops

Anthropics 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.

Were 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 wont be embedded in a single product team youll 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. Were building on frontier models that evolve constantly serving customers from individual developers to the largest enterprises across multiple surfaces (API 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. Youre obsessed with making it effortless for the field to share what theyre 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.

Youll 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 youll establish the intake synthesis and routing infrastructure that makes voice of the customer a first-class input to every roadmap. Youll drive adoption through influence making it so obviously useful that teams pull from it rather than get pushed to it.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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 youve 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 didnt 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 dont report to you.
• Are comfortable with ambiguity and can create structure where none exists youve 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.

• 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.

Minimum education: Bachelors 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 arent 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.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you some cases we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

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. Were 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.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policy for using AI in our application process.