Engineering Manager, Research Data Platform (AI)

TL;DR

Engineering Manager, Research Data Platform (AI): Building and scaling data-intensive systems to support large-scale AI research with an accent on data modeling, schema design, and platform architecture. Focus on designing canonical datasets and platform components that enable researchers to produce, query, and trust data efficiently.

Location: Must be based in or able to commute to San Francisco, CA or New York City, NY (Hybrid: minimum 25% in-office attendance required).

Salary: $405,000 - $850,000 USD

Company

Anthropic is an AI safety and research company dedicated to building reliable, interpretable, and steerable AI systems.

What you will do

• Collaborate with researchers to identify and solve data-related bottlenecks in their workflows.
• Set technical direction for the team and design scalable platform components and services.
• Own core datasets end-to-end, including pipelines, schemas, and documentation.
• Drive the convergence toward canonical, standardized datasets for research teams.
• Lead complex, multi-quarter projects while remaining hands-on in the code.
• Mentor engineers and raise the technical bar through design reviews and high-quality contributions.

Requirements

• Must be based in or able to work from San Francisco or New York City offices.
• Proven experience building and operating data-intensive systems at scale.
• Strong expertise in data modeling and schema design.
• Experience setting technical direction or owning architecture for data platforms.
• Ability to lead through influence and work effectively with exploratory research teams.
• Pragmatic approach to balancing quick solutions with durable, long-term architecture.

Nice to have

• Experience with large-scale ETL, Spark, BigQuery, ClickHouse, or DuckDB.
• Background in metrics, experiment-tracking systems, or high-volume time-series data.
• Experience building developer tooling or internal data platforms for technical users.
• Working knowledge of machine learning or experience working in an ML research lab.
• Interest in or experience with people management.

Culture & Benefits

• Competitive compensation and benefits package.
• Generous vacation and parental leave policies.
• Flexible working hours.
• Collaborative research-focused environment with frequent discussions.
• Optional equity donation matching.