Software Security Engineer, Labs (AI)

Location: San Francisco, CA; New York City, NY; or Seattle, WA. Hybrid policy: staff must work from one of the offices at least 25% of the time.

Annual salary: $320,000–$485,000 USD

Company

Anthropic develops reliable, interpretable, and steerable AI systems designed to be safe and beneficial.

What you will do

• Own Security Labs projects end to end, from selecting and scoping a research bet through prototyping, real-workload testing, handoff, or documented exit.
• Build experimental security infrastructure including isolated research clusters, attestation chains, hypervisor and runtime isolation, and verification tooling.
• Collaborate with pretraining, reinforcement learning, inference, and compute teams to test whether research workflows remain viable under proposed security controls.
• Turn experiments into concise technical writeups, long-term security architecture recommendations, and costed contingency plans.
• Help select future projects and influence improvements in AI security practice.

Requirements

• Strong software engineering skills and the ability to build infrastructure independently.
• Deep expertise in at least one specialized area such as firmware or hardware security, applied cryptography, OS/kernel/hypervisor internals, formal methods, reverse engineering, exploit development, or high-assurance systems.
• Experience building and shipping projects under independent direction, including prototypes or experiments intended to answer difficult questions.
• Ability to work across domains and layers of the stack, communicate clearly, and document technical findings.
• Strong programming skills in Python plus at least one of Rust, Go, or C/C++.
• Bachelor’s degree or equivalent education, training, and experience in a relevant field.

Nice to have

• Experience with air-gapped or high-side environments, classified networks, cross-domain solutions, ICS/SCADA, or financial trading infrastructure.
• Background in offensive security, red teaming, or vulnerability research.
• Familiarity with ML infrastructure, including training pipelines, distributed schedulers, inference serving, or accelerator hardware.
• Experience in startups, applied research groups, independent consulting, or small security organizations.

Culture & Benefits

• Fast-paced, high-risk security research with projects typically running for weeks rather than quarters.
• Collaborative research environment with frequent discussions focused on high-impact AI safety and security work.
• Competitive compensation, flexible working hours, generous vacation and parental leave, and office collaboration spaces.
• Optional equity donation matching.
• Visa sponsorship is available, with reasonable efforts and immigration-lawyer support for successful candidates.