Head of Business Technology Engineering
San Francisco, CA | New York City, NY
Posted 12h ago
About the job
Anthropic's Business Technology Engineering team is responsible for building and maintaining the internal systems that power the company. This includes owning internal platforms, collaboration tools, and embedding engineers within various business functions to integrate AI, specifically Claude, into their workflows. The team's goal is to make Anthropic a leader in internal AI utilization and serve as a model for customers. The role involves leading a growing engineering organization focused on both shared platforms and forward-deployed engineering initiatives, partnering with functional leaders, and shaping the future of internal engineering practices.
Responsibilities
- Lead and scale a global engineering organization, including hiring, leveling, and developing leads.
- Partner on defining and executing a roadmap for how business functions leverage Claude, including success metrics.
- Oversee the Platforms track, ensuring reliability, velocity, and scale of Claude Support and core employee platforms.
- Manage the Forward Deployed track, focusing on engagement, prioritization, handoffs, and adoption.
- Serve as a technical executive partner to leaders of Legal, Workplace, Comms, Product Ops, and Product Support.
- Collaborate with Labs and Product on dogfooding, providing feedback on evaluations and shipping internal builds.
- Represent Anthropic's internal operations to Enterprise customers.
- Set and maintain a high engineering bar for production-adjacent builds, evaluation rigor, reusable patterns, and responsible internal deployment.
Requirements
- 12+ years in software engineering, with 6+ years leading engineers.
- At least 3 years of experience managing managers.
- Experience leading an organization of 20+ engineers across multiple domains.
- Experience running internal-tools, business-systems, or platform engineering.
- Demonstrated ability to lead through technical judgment, understanding agent architecture, eval design, and failure modes.
- Ability to communicate technical trade-offs and drive decisions with diverse stakeholders.
- Capacity to maintain high craft standards while prioritizing effectively and communicating 'no' constructively.
- Desire for ownership in how a frontier AI lab operates internally using its own models responsibly.