Data Engineer (AI)

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid policy: staff are expected to work from one of the offices at least 25% of the time, with some roles requiring more office time.

Annual salary: $320,000–$405,000 USD.

Company

Anthropic develops reliable, interpretable, and steerable AI systems designed to be safe and beneficial for users and society.

What you will do

• Unify first-party product and revenue data with third-party sources through orchestration, modeling, and normalization.
• Build identity and entity-resolution systems, including record matching, deduplication, and trusted company relationships.
• Define canonical data attributes with clear sourcing, provenance, and freshness requirements.
• Create scores, signals, and AI-generated attributes for GTM prioritization and deliver them to systems such as the CRM.
• Operate data infrastructure with observability, quality, cost, security, and access controls.
• Partner with Sales Strategy and Operations, Finance, Data Science, and data engineering teams on definitions, planning, segmentation, routing, and platform reuse.

Requirements

• Experience as a data engineer or analytics engineer building and operating production pipelines and data models.
• Strong SQL and Python skills, plus experience with modern transformation and orchestration tools on a cloud data warehouse.
• Experience making data from multiple sources usable, including record matching, deduplication, and reconciliation of conflicting values.
• Familiarity with go-to-market data and CRM systems.
• Ability to evaluate data sources, define data with business partners, and make decisions about data quality.
• Clear written and verbal communication with technical and non-technical partners.
• Regular hands-on use of AI tools in engineering work.
• Minimum education: a bachelor’s degree or equivalent education, training, and/or experience in a relevant field.

Nice to have

• 5+ years of experience in data engineering, analytics engineering, or GTM data roles.
• Experience building shared data products or platforms used and contributed to by multiple teams.
• Experience with firmographics, corporate hierarchies, or master data management.
• Experience using LLMs in data pipelines and evaluating their output.
• Hands-on Salesforce experience, including work with large data volumes.
• Experience supporting GTM planning such as territory design, segmentation, or scoring.

Culture & Benefits

• Collaborative work across research, engineering, policy, business, Sales Strategy and Operations, Finance, Data Science, and data engineering.
• Flexible working hours and a hybrid office policy.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Visa sponsorship may be available; Anthropic makes reasonable efforts to support visas and works with an immigration lawyer.
• Frequent research discussions and an emphasis on communication and diverse perspectives.

Hiring process

• Review Anthropic’s candidate AI-usage guidance before using AI during the application process.
• For recruiting communications, verify that contacts use an @anthropic.com address or identify a vetted recruiting agency; legitimate recruiters will not request money, fees, or banking information before the first day.