Sales Operations
Business Operations
hybrid: San Francisco, CA
Salary range $190,000 - $270,000
added Wed Sep 27, 2023
Apply to AnthropicAs the founding member of our Sales Operations team, you will be instrumental in helping Anthropic build a high-growth business that's scalable and predictable. You’ll own designing and building our Sales Operations function and you will be responsible for the overall productivity and effectiveness of the Sales organization. You’ll partner closely with our Sales and Finance teams to build strategic frameworks, own our tools and metrics, and make data-driven decisions. This role is a great fit for someone who’s both seen excellence at scale and operated in rapidly scaling, high-ambiguity teams and scope.
About Anthropic
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and for society as a whole. Our interdisciplinary team has experience across ML, physics, policy, business and product.
Responsibilities:
- Designing and implementing processes that improve the efficiency and productivity of our sales team
- Managing and supporting forecasting, pipeline analysis, annual planning, and sales cadence
- Owning all sales systems and tools
- Working cross-functionally to implement new reporting and planning solutions
- Setting clear goals and direction for the Sales Operations team
- Building a great culture and ensuring team members are happy, effective, and growing in their career
You may be a good fit if you:
- Have 10+ years of experience in sales operations (or related functions) and at least 5 years of people management experience
- Are a builder with a strong track record of designing and implementing effective solutions that scale
- Are exceptionally collaborative and have experience working with stakeholders across functions
- Have a strong operational background with a track record of making data driven decisions
- Have a high threshold for navigating ambiguity and are able to balance setting strategic priorities with rapid, high-quality execution
- Thrive in unstructured environments, and have a knack for bringing order to chaos
Annual Salary:
- The expected salary range for this position is $190k - $270k.
Logistics
Location-based hybrid policy: Currently, we expect all staff to be in our office at least 25% of the time.
Deadline to apply: None. Applications will be reviewed on a rolling basis.
US visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate; operations roles are especially difficult to support. But if we make you an offer, we will make every effort to get you into the United States, 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.
Compensation and Benefits*
Anthropic’s compensation package consists of three elements: salary, equity, and benefits. We are committed to pay fairness and aim for these three elements collectively to be highly competitive with market rates.
Equity - On top of this position's salary (listed above), equity will be a major component of the total compensation. We aim to offer higher-than-average equity compensation for a company of our size, and communicate equity amounts at the time of offer issuance.
Benefits - Benefits we offer include:
- Optional equity donation matching at a 3:1 ratio, up to 50% of your equity grant.
- Comprehensive health, dental, and vision insurance for you and all your dependents.
- 401(k) plan with 4% matching.
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
- Stipends for education, home office improvements, commuting, and wellness.
- Fertility benefits via Carrot.
- Daily lunches and snacks in our office.
- Relocation support for those moving to the Bay Area.
* This compensation and benefits information is based on Anthropic’s good faith estimate for this position, in San Francisco, CA, as of the date of publication and may be modified in the future. The level of pay within the range will depend on a variety of job-related factors, including where you place on our internal performance ladders, which is based on factors including past work experience, relevant education, and performance on our interviews or in a work trial.
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our customers and for society as a whole.
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.