Growth Engineering Lead: Scale AI Growth

Anthropic; San Francisco (CA); On-site; USD 405,000 - 485,000; Full time

Benefits offered by this job

Equity donation matching

Generous vacation & parental leave

Flexible working hours

Office in San Francisco

Job summary

Anthropic, based in San Francisco, seeks a growth engineering leader to build and lead our Growth Engineering team as founders of the growth initiative. The role demands deep expertise in user acquisition, engagement, and retention through data-driven strategies and technical implementations.

You will define the technical growth strategy, establish experimentation frameworks, and scale impact through scalable systems for experimentation, personalization, and optimization.

Qualifications

• Strong background leading growth engineering teams and shipping growth initiatives.
• Experience driving acquisition, activation, engagement, and retention through data-driven approaches.
• Proven ability to recruit, scale, and retain engineers in a high-growth environment.

Responsibilities

• Build and lead a high-performing growth engineering team.
• Define and execute the technical strategy for growth initiatives, including A/B testing and measurement systems.
• Create clarity and direction in a fast-moving environment; collaborate with product, marketing, and data science teams.
• Drive scalable systems for experimentation, personalization, and optimization.

Skills

Growth engineering

A/B testing

Data-driven optimization

Leadership

Full-stack development

Education

Bachelor's degree

Tools

Experimentation frameworks

Data analysis tools

Job description

Anthropic, based in San Francisco, seeks a growth engineering leader to build and lead our Growth Engineering team as founders of the growth initiative. The role demands deep expertise in user acquisition, engagement, and retention through data-driven strategies and technical implementations.

You will define the technical growth strategy, establish experimentation frameworks, and scale impact through scalable systems for experimentation, personalization, and optimization.