Engineering Manager, Cloud Safety

Key Responsibilities

• Set technical strategy and oversee development of safety features across all Claude CSP surfaces
• Collaborate across teams and companies to deeply understand product, infrastructure, operations and capacity needs, identifying potential solutions to support frontier LLM serving
• Work closely with cross-functional stakeholders across companies to align on goals and drive outcomes
• Create clarity for the team and stakeholders in an ambiguous and evolving environment
• Take an inclusive approach to hiring and coaching top technical talent, and support a high performing team
• Design and run processes (e.g. postmortem review, incident response, on-call rotations) that help the team operate effectively and never fail the same way twice

Minimum Qualifications

• 8+ years of experience in high-scale, high-reliability software development, particularly infrastructure or capacity management
• 3+ years of engineering management experience
• Experience recruiting, scaling, and retaining engineering talent in a high growth environment
• Experience scaling products, resources and operations to accommodate rapid growth
• Deep interest in the potential transformative effects of advanced AI systems and commitment to ensuring their safe development
• Excel at building strong relationships and strategy with stakeholders across engineering, product, finance, and policy
• Experience working with external partners to align goals and deliver impact
• Comfortable working in a fast-paced, early environment; able to adapt priorities as driven by the rapidly evolving AI space
• Excellent written and verbal communication skills
• Demonstrated success building a culture of belonging and engineering excellence
• Motivated by developing AI responsibly and safely
• Willing and able to travel frequently between Seattle and the SF Bay Area

Preferred Qualifications

• Experience with identity and access controls — KYC/KYB, verification flows, tiered access
• Experience with detecting and mitigating platform abuse at scale — account fraud, bot traffic, model extraction
• Experience with trust & safety, security, and/or legal/compliance
• Experience or interest in machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Experience with deployment and capacity management automation

Education

• Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

Benefits

• Competitive compensation and benefits
• Optional equity donation matching
• Generous vacation and parental leave
• Flexible working hours
• Office space for collaboration