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
In the Revenue Operations Systems role at Anthropic, you will spearhead our revenue operations tooling strategy, building and maintaining the systems that drive our business growth. Your expertise will be instrumental in building a high-growth business that's both scalable and predictable. You'll own the technical architecture for all Go-To-Market (GTM) systems, determine the critical components of our revenue technology stack, and manage marketing automation systems. You'll leverage cutting-edge AI technologies to enhance productivity across our revenue-generating functions, and will be instrumental in accelerating revenue growth and optimizing operations.
Responsibilities:
- Lead the development and execution of Anthropic's Revenue Operations tooling strategy, with a focus on building and maintaining systems that drive revenue growth
- Architect, build, and administer our overall GTM technology stack, including Salesforce, Apollo, Hubspot, Clay, Gong, and other tools, continuously seeking opportunities to integrate AI for enhanced productivity and insights
- Manage email operations and oversee the technical implementation of intelligent drip campaigns, ensuring delivery to the correct audience to maximize conversion rates
- Spearhead the integration of AI technologies into our revenue systems to improve forecasting, automate processes, and provide predictive analytics
- Own and administer Salesforce Data Cloud and CRM Analytics, leveraging frontier technology to create an AI-driven technology stack
- Develop GTM data model and set up intelligent data architecture to support flexible and scalable reporting, ensuring accurate marketing attribution and full-funnel revenue reporting
- Select, implement, and optimize new tools and technologies to improve revenue efficiency and drive growth
- Collaborate cross-functionally with Product, Engineering, Data Science, Legal, Accounting, and Finance teams to integrate systems and create compliant processes
- Support end-user adoption of AI-enhanced tools and proactively design solutions based on user feedback to enhance productivity and revenue generation capabilities
You may be a good fit if you:
- Have 7+ years of experience in Revenue Operations systems architecture, including 3+ years of experience working on complex Salesforce Flows
- Have both built Salesforce instances from scratch and scaled them to 300+ user instances with sophisticated product and data pipeline integrations
- Are passionate about integrating AI into business processes and have experience implementing AI solutions to drive operational efficiency and revenue growth
- Have a proven track record of implementing technology solutions that directly contribute to revenue acceleration and growth
- Are experienced with marketing automation systems and complex attribution models
- Can adapt revenue technology solutions to non-traditional business models and market cycles, always with an eye on increasing overall revenue
- Thrive in unstructured environments and love bringing order to chaos
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected salary range for this position is:
Annual Salary:
$170,000—$270,000 USD
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.
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 - For eligible roles, 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.
US Benefits - The following benefits are for our US-based employees:
- Optional equity donation matching.
- Comprehensive health, dental, and vision insurance for you and all your dependents.
- 401(k) plan with 4% matching.
- 22 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.
UK Benefits - The following benefits are for our UK-based employees:
- Optional equity donation matching.
- Private health, dental, and vision insurance for you and your dependents.
- Pension contribution (matching 4% of your salary).
- 21 weeks of paid parental leave.
- Unlimited PTO – most staff take between 4-6 weeks each year, sometimes more!
- Health cash plan.
- Life insurance and income protection.
- Daily lunches and snacks in our office.
* This compensation and benefits information is based on Anthropic’s good faith estimate for this position as of the date of publication and may be modified in the future. Employees based outside of the UK or US will receive a different benefits package. 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.
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.
Top Skills
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.
