The opportunity
Frontier AI is on track to be among the most consequential and most adversarially-targeted technology in the world. The capability curve is steep, the adversaries who want these systems are extremely well-resourced, and the security bar this will eventually require is well beyond where the industry operates today.
What you'll do
Can our core research workflows survive extreme isolation?
Can we replace trust with cryptographic guarantees?
Can the models themselves become our most effective security control?
What would it actually take to defend against a tier-1 state adversary, and how much of that can we build now?
Standing up a prototype high-assurance research cluster: running real Anthropic training and research workloads under extreme isolation and physical security controls, and finding out exactly where productivity breaks and what we'd need to invent to get it back
Provable inference: cryptographic verification (zero-knowledge proofs, attestation chains) that a given output came from a specific model running specific code, replacing "trust us" with math
What they're looking for
- Experience inside airgapped or high-side environments (classified networks,: cross-domain solutions, ICS/SCADA, financial trading infrastructure) and the operational realities of working in them
- A background in offensive security, red teaming, or vulnerability research,: with calibrated intuitions for which threats actually matter
- Familiarity with ML infrastructure (training pipelines, distributed: schedulers, inference serving, accelerator hardware) sufficient for grounded conversations with researchers about what their workloads actually need
- A history of working in environments built around rapid iteration rather than: rigid change control: startups, applied research groups, independent consulting, small security shops
