Engineering Manager, Data Infrastructure

About the position

Anthropic is seeking an experienced Engineering Manager to lead our Data Infrastructure team. In this role, you'll guide a team responsible for designing, building, and maintaining the data infrastructure that powers our AI research and products. Your work will be crucial in ensuring Anthropic can continue to reliably and safely train frontier models while maintaining the highest standards of data quality and accessibility. The Data Infrastructure team is responsible for building and operating the systems that enable us to process, store, and serve massive datasets efficiently and reliably. You'll work closely with research teams to understand their data requirements, deliver efficient and reliable data solutions, and continuously improve our data infrastructure.

Responsibilities

• Lead and grow a team of data infrastructure engineers, providing technical guidance, career development, and performance management
• Partner with research and engineering teams to understand data requirements and architect solutions that meet their needs
• Set technical strategy and oversee development of high-scale, reliable data infrastructure systems
• Design and implement data governance best practices across the organization
• Drive improvements in our data pipeline efficiency, reliability, and maintainability
• Establish processes for effective team operations and continuous improvement
• Mentor top technical talent and help build a strong engineering culture
• Partner with recruiting to build out a world-class data infrastructure team

Requirements

• Have 5+ years of engineering experience, with 3+ years of engineering management experience
• Have deep expertise in building and scaling data infrastructure, including experience with technologies like Airflow, dbt, data warehouses (BigQuery, Snowflake, Databricks), and cloud services (GCP/AWS)
• Are passionate about developing engineers and building inclusive, high-performing teams
• Have excellent communication skills and can build consensus across diverse stakeholders
• Have experience setting technical strategy and roadmaps for complex infrastructure systems
• Are comfortable operating in ambiguous, fast-paced environments
• Have a track record of delivering reliable systems at scale
• Care deeply about data quality, reliability, and security

Nice-to-haves

• Have experience working with ML infrastructure and large-scale AI training systems
• Have expertise in distributed systems and cloud architecture
• Bring experience with real-time data processing systems and streaming architectures
• Have experience managing teams during periods of rapid growth
• Have knowledge of data privacy and security best practices
• Demonstrate experience implementing data governance frameworks
• Show familiarity with modern ML development workflows and requirements

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Lovely office space in which to collaborate with colleagues