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.
Anthropic is looking for a Product Owner, Enrichment to own and drive the strategy, architecture, and execution of our data enrichment ecosystem. This role sits at the intersection of Revenue Operations, Data Engineering, and Go-to-Market strategy, and is responsible for building and maintaining a best-in-class enrichment infrastructure that delivers a reliable, comprehensive source of truth for company and contact data across global markets.
You will be the subject matter expert and product owner for all enrichment tools, data sources, and processes—including platforms like Clay, Dun & Bradstreet, ZoomInfo, and other third-party providers. You will design and operate the systems that power account hierarchies, firmographic enrichment, contact discovery, and signal detection, ensuring our GTM teams have the accurate, complete data they need to identify, prioritize, and close business.
This is a hands-on, technically-oriented role that requires deep experience working with large datasets, complex system integrations, and Salesforce data modeling. You will collaborate closely with Sales, Marketing, Data Science, Data Engineering, and Revenue Operations to ensure our enrichment strategy supports both near-term GTM execution and long-term data infrastructure goals.
Own the end-to-end enrichment strategy and roadmap, serving as the product owner for all enrichment tools, vendors, and data sources including Clay, Dun & Bradstreet, ZoomInfo, and emerging providers
Build and maintain a unified enrichment master—a reliable source of truth for company and person data including parent-child account hierarchies, firmographics, technographics, and contact intelligence across domestic and international markets
Design and implement waterfall enrichment workflows that orchestrate multiple data providers to maximize coverage, accuracy, and cost efficiency while minimizing redundancy
Architect enrichment data models within Salesforce, making strategic decisions about how enrichment data is stored, related, and surfaced (e.g., custom objects vs. direct field integration, parent account structures, enrichment audit trails)
Hands-on data manipulation and transformation—write queries, build data pipelines, and work directly with data warehouses (e.g., Snowflake, BigQuery) to clean, transform, match, and deduplicate enrichment data at scale
Lead international enrichment strategy, addressing the unique challenges of enriching company and contact data across global markets with varying data availability, provider coverage, and regulatory requirements
Partner with Data Science and Data Engineering to define enrichment schemas, resolve entity matching challenges, and build scalable infrastructure that supports both real-time and batch enrichment processes
Collaborate with Sales, Marketing, and Revenue Operations to understand GTM data needs, translate business requirements into enrichment solutions, and ensure enrichment outputs directly support pipeline generation, territory planning, lead routing, and account scoring
Define and track enrichment KPIs including match rates, data completeness, freshness, accuracy, and downstream GTM impact—using metrics to continuously improve the enrichment ecosystem
Evaluate and onboard new enrichment vendors and data sources, conducting proof-of-concept testing and negotiating contracts in partnership with procurement
Explore and implement AI-powered enrichment capabilities, including prompt-based enrichment using LLMs to supplement traditional data providers for emerging companies, startups, and hard-to-enrich segments
10+ years of experience in data enrichment, data operations, or revenue/marketing operations with hands-on ownership of enrichment tools and strategy in a B2B SaaS or enterprise technology environment
Deep expertise with enrichment platforms such as Clay, Dun & Bradstreet (D-U-N-S, Data Blocks, hierarchies), ZoomInfo, Clearbit, People Data Labs, or comparable providers, including experience building waterfall enrichment workflows and enrichment masters
Strong Salesforce experience (required)—including data modeling for enrichment (custom objects, account hierarchies, parent-child relationships), integration architecture, and understanding of how enrichment data flows through the CRM to support GTM processes
Hands-on technical skills for data manipulation including SQL proficiency, experience with data warehouses (Snowflake, BigQuery, or similar), and comfort working with ETL/reverse ETL pipelines, APIs, and data transformation tools
Proven experience with international enrichment—building enrichment coverage across global markets with varying data quality, provider availability, and regulatory landscapes (GDPR, data residency, etc.)
Strong product ownership mindset with experience managing roadmaps, backlogs, and stakeholder priorities—able to translate business needs into technical requirements and drive execution across cross-functional teams
Dual data + RevOps mindset—equally comfortable working with Data Science and Data Engineering on infrastructure and schema design as you are partnering with Sales and GTM teams on pipeline and territory optimization
Excellent communication skills to bridge technical and business audiences, lead stakeholder discovery sessions, and present enrichment strategy and impact to leadership
Experience building or leveraging AI-powered enrichment prompts (e.g., using LLMs to research and enrich company data, identify signals, or fill gaps where traditional providers lack coverage)
Familiarity with data quality and MDM (Master Data Management) frameworks and tools
Experience with routing and scoring tools such as LeanData, and marketing automation platforms
Background in startup signal detection—identifying high-potential early-stage companies through funding, hiring, technographic, and intent signals
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.
Education requirements: We require at least a Bachelor's degree in a related field or equivalent experience.
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.
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.
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