About the Role
As the Engineering Manager for Agent Platform at Anthropic, you'll lead the strategic development of Claude's autonomous capabilities, managing teams that are fundamental to expanding how Claude handles complex, multi-step workflows. You'll oversee the infrastructure that enables Claude to acquire specialized capabilities and domain expertise, as well as the evaluation frameworks that measure and improve Claude's performance on extended, agentic tasks.
This role sits at the intersection of cutting-edge AI research and practical product development. You'll partner with enterprise customers and research teams to translate breakthrough capabilities into production-ready features, while building the systems that ensure quality and safety at scale. Your teams will enable both Anthropic and our customers to extend Claude's capabilities for sophisticated real-world tasks.
The Agent Platform group is part of Frontier Apps, focused on productizing research breakthroughs and enabling Claude to tackle increasingly sophisticated activities. You'll work closely with research teams developing foundational infrastructure, ensuring smooth productization pathways from research to customer-facing features.
Responsibilities
Engineering Leadership & Team Management
- Lead and grow multiple high-impact engineering teams focused on agent capabilities
- Partner with technical leads to set technical direction, prioritize roadmaps, and ensure delivery of high-quality, scalable systems
- Foster a culture of rapid iteration, technical excellence, and cross-functional collaboration
- Manage team processes, from planning to implementation to incident response
Product & Strategic Execution
- Drive the productization of agent capabilities, enabling both internal teams and external customers to use Claude in more powerful ways
- Work with cross functional teams, customers, and partners to help bring your developments to market successfully and ensure adoption of new functionality
- Evolve evaluation infrastructure to support continuous quality measurement throughout model development and deployment
- Partner with enterprise customers across financial services, life sciences, and other verticals to identify high-value use cases and translate them into reusable capabilities
Cross-Functional Collaboration
- Collaborate with API and platform teams to define strategies for broad access to new capabilities, performance, and enterprise governance
- Partner closely with research teams on alignment, capability evaluation, and productization of experimental features
- Work with Product teams to ensure agent infrastructure supports broader product roadmap
- Interface with growth and enterprise teams to enable capability distribution and governance models
- Coordinate with security and safety teams to ensure agent capabilities maintain appropriate standards and drive enhancements in safety and security
Technical Strategy & Operations
- Define strategies for scaling agent capabilities to thousands of use cases and millions of users while maintaining quality, performance, and reliability.
- Establish technical standards and best practices for capability development, both for internal teams and external partners
- Drive decisions on infrastructure ownership and architectural boundaries
- Navigate complex architectural questions around autonomous workflows, third-party integrations, and event-driven systems
You may be a good fit if you
- Have 5+ years of engineering management experience, ideally managing multiple teams and complex product areas
- Care deeply about building AI systems that are safe, reliable, and beneficial for users
- Have experience scaling teams and processes during periods of rapid growth
- Can navigate ambiguity and rapidly changing requirements while maintaining team focus and delivering results
- Excel at cross-functional collaboration, particularly with research teams, enterprise customers, and product stakeholders
- Are comfortable with the "pick up slack" mentality - doing whatever needs to be done to unblock your teams and drive impact
- Can balance speed of iteration with maintaining high quality standards
Strong candidates may also have experience with
- Building evaluation frameworks or infrastructure for machine learning systems
- Working with enterprise customers to understand complex, domain-specific requirements and build generalized platforms
- Developer tools, SDKs, or platforms that enable third-party extensibility
- Managing teams at the intersection of research and product development
- Large language models, prompt engineering, or AI agent systems
- Event-driven architectures or autonomous systems
- Fast-paced startup environments where you've built from 0 to 1
- Managing technical partnerships or ecosystem development
Deadline to apply: None. Applications will be reviewed on a rolling basis.
