Cloud Security Engineer supporting and securing client environments across AWS and hybrid infrastructures. Collaborating with Cloud Operations to monitor, investigate, and remediate security events.
About the role
- Conduct empirical AI safety research with mentorship in the Anthropic Fellows Program. Focused on security issues in AI systems with potential career growth opportunities.
Responsibilities
- The Anthropic Fellows Program is designed to accelerate AI security and safety research, and foster research talent.
- Provide funding and mentorship to promising technical talent - regardless of previous experience - to research the frontier of AI security and safety for four months.
- Use external infrastructure (e.g., open-source models, public APIs) to work on an empirical project aligned with research priorities, with the goal of producing a public output (e.g., a paper submission).
- Run multiple cohorts of Fellows each year. This application is for the next two cohorts, starting in May and July 2026.
- Direct mentorship from Anthropic researchers
- Access to a shared workspace (in either Berkeley, California or London, UK)
- Connection to the broader AI safety research community
Requirements
- Strong technical background in computer science, mathematics, physics, cybersecurity, or related fields
- Motivated by reducing catastrophic risks from advanced AI systems
- Excited to transition into full-time empirical AI safety research and would be interested in a full-time role at Anthropic
- Fluent in Python programming
- Available to work full-time on the Fellows program for 4 months
- Thrive in fast-paced, collaborative environments
- Can implement ideas quickly and communicate clearly
- Strong candidates may also have:
- • Contributed to open-source projects in LLM- or security-adjacent repositories
- • Demonstrated success in bringing clarity and ownership to ambiguous technical problems
- • Experience with pentesting, vulnerability research, or other offensive security
- • A history demonstrating desire to do the "dirty work" that results in high-quality outputs
- • Reported CVEs, or been awarded for bug bounty vulnerabilities
- • Experience with empirical ML research projects
- • Experience with deep learning frameworks and experiment management
Benefits
- Weekly stipend of 3,850 USD / 2,310 GBP / 4,300 CAN & access to benefits (benefits vary by country)
- Funding for compute (~$15k/month) and other research expenses
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