Engineering Manager, Research Data Platform (AI)

Location: San Francisco, CA or New York City, NY; hybrid policy requires staff to work from an office at least 25% of the time

Annual salary: $405,000–$850,000 USD

Company

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

What you will do

• Work with researchers and supporting engineers to understand workflows, identify high-impact opportunities, and shape platform priorities.
• Set technical direction across research data platform components and datasets.
• Design and build libraries, services, and interfaces that integrate with training frameworks.
• Own core datasets end to end, including pipelines, schemas, documentation, and data-quality guarantees.
• Drive adoption of canonical datasets, including the core data model for reinforcement-learning transcripts.
• Lead complex multi-quarter projects across systems and teams while contributing hands-on code, design reviews, and mentorship.

Requirements

• Experience building and operating data-intensive systems at scale, including pipelines, storage layers, or query systems.
• Strong data modeling and schema design skills, with experience setting technical direction or owning an architecture used by other teams.
• Ability to work directly with internal users, discover requirements through experimentation, and optimize for adoption.
• Ability to lead through influence, align engineers and stakeholders, and deliver pragmatic, high-leverage solutions.
• Minimum education: bachelor's degree or equivalent education, training, or experience in a relevant field.
• Ability to work from San Francisco or New York City under the hybrid office policy; visa sponsorship is available subject to role and candidate eligibility.

Nice to have

• Experience with large-scale ETL and analytical or columnar storage such as Spark, BigQuery, ClickHouse, DuckDB, or Parquet.
• Experience with metrics, experiment-tracking, high-volume time-series, dataset cataloging, or lineage systems.
• Experience building developer tooling or internal data platforms for demanding technical users.
• Working knowledge of machine learning or experience working with an ML research lab.
• Interest in people management and growing engineers.

Culture & Benefits

• Collaborative research environment focused on large-scale AI efforts and long-term impact.
• Frequent research discussions and close collaboration across research, engineering, policy, and business functions.
• Competitive compensation, optional equity donation matching, generous vacation, and parental leave.
• Flexible working hours and an office environment designed for collaboration.