Product Operations Manager, Embedded
Anthropic · San Francisco, CA | New York City, NY | Seattle, WA ·
- Category
- Embedded
- Visa sponsorship
- Yes
- Company size
- 501-1000
- Salary
- USD 240,000 – 260,000 / year
Embeds with AI product teams to run launches, early-access programs, and feedback loops, ensuring safe and reliable model deployments while streamlining cross-functional processes.
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.
About the Role:
We're hiring several Product Operations Managers to embed within our core product teams. Each will contribute to a key component of our stack. Whether you are ensuring models work within each of our harnesses, prioritizing a great experience across cloud offerings, or building the application layer that keeps users on the frontier, the Product Operations team is an integral part of delivering great products to the world.
Product Operations is the connective tissue between Research, Product, and the market. We shorten the distance between what our models can do and what people get to use. Each of us sits inside one product team as an extension of its leadership, and together we run one shared operating system for how Anthropic ships and learns.
On a given day you might get a launch through its final review, run an early access window, or triaging customer feedback. The rest of the week you build the systems so the team ships and learns faster next time. Our team is small and gets unusual leverage from Claude enabling us to fill gaps across the company and deliver outsized value.
Responsibilities:
1. Ship with confidence
- Own launch readiness for your team. Keep our launch calendar the source of truth for what is shipping and when.
- Get every major launch through go/no-go: pre-read written, Security, Safeguards, Legal, and Commercial sign-offs recorded, and any accepted risk written down on purpose.
- Run early access and beta programs that return signal Product and Research can act on. Define the question before the window opens, give testers the scaffolding to answer it, and close each one with a retro on whether the feedback landed.
- Program manage new model launches on your surface: readiness goals set in advance, testing and eval coverage tracked, issues triaged, prompting changes landed, retro run. You won't write the evals. You run the program around them.
2. Close the loop with users
- Turn a lot of noise into two clear signals: what users are asking for, ranked by impact and mapped to the roadmap, and which customers or cohorts are blocked, on what, and why it matters.
- Plug your team into Anthropic's shared feedback systems rather than building a private one, and improve the shared systems where they fall short.
- Make sure the field, Support, and Research hear back about what happened with what they sent.
3. Run the team's operating system
- Set the team's pace: planning, business and execution reviews, goal tracking, offsites.
- Own how your team works with Legal, Safeguards, Security, GTM, and other product teams so partnering with your team is predictable.
- Push reporting overhead toward zero. Reviews and digests should be generated from data that already exists.
- Fill the gaps. Every embedded seat carries one or two projects unique to its team, for example managing Monthly Business Reviews and helping track progress between cycles.
4. Build with Claude
- Build the tools you need yourself: Claude-powered triage, dashboards that read and write to our systems of record, skills and agents that take the chasing out of the job.
- Contribute what you build back to the ProdOps team as reusable patterns (launch checklists, EAP setup, lookbacks, deprecations) so nobody starts from scratch.
You may be a good fit if you have:
- Have owned an operational program end to end (launches, early access, feedback, or planning) that a product team relied on to make decisions. You designed it and ran it, not just executed someone else's plan.
- Have built a process from zero to one and then simplified it as it scaled. You treat process as a product: it has users, metrics, and a happy path people want to follow.
- Have worked embedded with product leadership and can move a team without formal authority.
- Build with AI yourself. You have shipped Claude or other LLM-powered workflows, written the prompts, iterated on the outputs, and can describe model behavior with specifics.
- Have direct experience managing evals, refining system prompts, and adapting harnesses to new models.
- Have direct experience working with Cloud providers in partnership or GTM capacity
- Have commitment to safe deployment of AI. Bonus if experience with AI Safety and Safeguards.
Bonus:
- Program managed model launches or model quality at an application-layer AI product.
- Run early access, beta, or design partner programs.
- Product management, technical program management, chief of staff, or strategy and operations experience at a startup or fast-growing product company.
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.
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.
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 you're interested in this work. We think AI systems like the ones we're 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 from @anthropic.com email addresses. In 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 you're ever unsure about a communication, don't click any links—visit directly for confirmed position openings.
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.
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.
Come work with us!
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 about our policy for using AI in our application process.