GTM Strategy & Operations, Frontier

Posted Yesterday
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San Francisco, CA, USA
In-Office
270K-270K Annually
Entry level
Artificial Intelligence • Natural Language Processing • Generative AI
The Role
Lead go-to-market strategy and operations for frontier model and product launches. Own account selection, field readiness, launch-week coordination, customer adoption analysis, feedback loops, NPI methodology, executive reporting, capacity planning, and cross-functional alignment across GTM, Product, Research, Finance, Applied AI, Security, and Compute. Develop repeatable launch processes and actionable insights in a rapidly changing AI product environment.
Summary Generated by Built In
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

The GTM Strategy & Operations, Frontier team coordinates how Anthropic's research reaches the market: how we run model launches commercially, how we partner with Capacity teams to allocate a finite compute supply across customers and surfaces, and how we translate what the field learns into reads that Research, Product, Finance, and GTM leadership act on.

One tangible example of the work this role will contribute to is new model and product introduction: the end-to-end commercial run of a model, product or capability release, from identifying market opportunities to preparing customer cohorts and the field through to the adoption readout that shapes where we go from there. We are hiring for someone who can run a high-stakes cross-functional program where the bar for execution is sky high, author the strategic analysis and readouts executive leadership needs, and create and optimize repeatable methodologies.

This role reports to the Global Head of GTM Strategy & Operations, Frontier, and sits at the interface between GTM, Applied AI, Product, Research, Security & Safeguards, Finance, and Compute.

Key responsibilitiesRun launches
  • Serve as GTM DRI for product and model launches: own account selection for pre-launch, coordinate field readiness across scaled pre- and post-sales teams, and run the launch-week operating room with extreme ownership.  
  • Synthesize customer adoption signal (usage patterns, migration behavior, qualitative feedback from the field) into actionable reads for executive leadership across the company
  • Design and run the field response loop: how AE, CS, Applied AI and customer response and feedback gets captured, triaged, and routed to the teams who can act on it
Evolve the NPI methodology
  • Design and iterate GTM's NPI methodology across both standard releases and managed-access programs, including operating cadence, roles and handoffs with field teams, and the bar for launch readiness
  • Carry the executive reporting cadence for launches: what leadership teams see, how often, and how we make adoption trends legible early as well as retrospectively in an continual sprint environment
Partner across the company
  • Act as GTM's primary interface to Product S&O and Research on launch planning, ensuring commercial readiness is sequenced with product / model readiness
  • Work with Sales Strategy & Operations partners, Applied AI, and Customer Success on field execution, ensuring the launch motion lands consistently across segments and regions
  • Partner with Capacity teams on rate limits, provisioning, and capacity planning for account cohorts, assessing capacity-efficiency opportunity and executing against it with customer value at the core
  • Collaborate on protect-play targeting, sequencing, and post-launch competitive response when external launches and ours overlap
Minimum qualifications
  • Experience in product operations, PMM operations, release management, management consulting, or GTM strategy & operations
  • Built and run high-stakes, operations-heavy programs with many cross-functional dependencies at a high-velocity product company, with a track record of turning effective heroics into a repeatable, scaled methodology
  • Ability to quickly weigh, select, and execute the balance between business, safety, and repeatability considerations
  • Written for and presented to senior executives; you can produce the readout leadership reads and hold the room with Product, Research, and Finance counterparts
  • Exceptional analytical skills, rooted in data but never without corresponding actionable insights. You can design the metrics and reporting that make a program legible, distinguish signal from noise in a messy week-one read, and work with analytics engineering teams to evolve data design to be fit for purpose
  • A bias toward extreme ownership - you see the gap, you fill it, and you hold the outcome regardless of where the org lines fall
  • Bachelor's degree required
Preferred qualifications
  • Strong analytical foundation: SQL and code-level data proficiency, sophisticated modeling in Sheets or Excel, and experience with BI tools (Looker, BigQuery, or similar)
  • Experience at an AI, developer-tools, or API-first company with consumption-based pricing (ideally as well as B2B SaaS)
  • Strong familiarity with, if not direct experience in, commercial roles (sales, rev ops, product marketing) or product management in addition to operations
  • Familiarity with safety, trust & safety, or security-review processes in a product context
  • Demonstrated success operating in ambiguity at a company where the product and the operating model are both changing fast

Deadline to apply: None. Applications will be reviewed on a rolling basis. 

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:
$270,000$270,000 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.

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 anthropic.com/careers 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.

Skills Required

  • Experience in product operations, PMM operations, release management, management consulting, or GTM strategy and operations
  • Experience building and running high-stakes, operations-heavy programs with extensive cross-functional dependencies at a high-velocity product company
  • Ability to balance business, safety, and repeatability considerations and execute accordingly
  • Experience writing for and presenting to senior executives
  • Exceptional analytical skills and ability to produce actionable insights from data
  • Ability to design metrics and reporting, distinguish signal from noise, and collaborate with analytics engineering teams on data design
  • Strong ownership and ability to independently drive outcomes across organizational boundaries
  • Bachelor's degree or equivalent combination of education, training, and experience
  • SQL and code-level data proficiency
  • Sophisticated modeling skills in Google Sheets or Microsoft Excel
  • Experience with BI tools such as Looker or BigQuery
  • Experience at an AI, developer-tools, API-first, or B2B SaaS company with consumption-based pricing
  • Familiarity with commercial roles such as sales, revenue operations, product marketing, or product management
  • Familiarity with safety, trust and safety, or security-review processes in a product context
  • Demonstrated success operating in ambiguity at a rapidly changing company

Anthropic Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Anthropic and has not been reviewed or approved by Anthropic.

  • Strong & Reliable Incentives Pay is positioned as top-of-market for many technical roles through a mix of high base pay, equity, and occasional bonuses/signing incentives. Benefits like substantial monthly stipends and employer-paid protections further strengthen perceived total rewards.
  • Healthcare Strength Healthcare is described as comprehensive across medical, dental, and vision, with additional mental-health support. Coverage is framed as robust for employees and dependents, which can materially increase the value of the overall package.
  • Parental & Family Support Paid parental leave is described as notably generous, alongside fertility coverage and other family-oriented supports. These elements broaden the rewards package beyond cash compensation and can improve retention for caregivers.

Anthropic Insights

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The Company
HQ: San Francisco, California
2,500 Employees

What We Do

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.

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