The challenge now is modernising security to stop AI-enabled threats, whether they come from internal agents going rogue or from attackers using AI to become more dangerous.
Refractal was founded on cybersecurity and AI expertise from MIT, Microsoft, NASA and the U.
Our product lets organisations detect AI-enabled threats at low cost without sacrificing detection quality.
We take a practical approach to AI risk, combining proven cybersecurity methods with frontier AI security research.
Today, we work with governments and organisations that can't afford to get security wrong.
We're backed by leading deep-tech and cybersecurity investors and are growing the team to deliver on this mission.
The roleOwn the services and infrastructure that keep Refractal secure and reliable in production.
You will work across the enforcement runtime, data integrity, tenant isolation, agent tracing, model services, and cloud infrastructure.
Build systems that connect activity across agents, services, and tools, evaluate risk, apply decisions, and preserve the evidence behind them.
What you'll work onBuild and operate a low-latency runtime enforcement pipeline with predictable failure behaviour.
Build tamper-evident evidence storage and enforce multi-tenant isolation throughout every data path.
Create reliable event and streaming services with safe handling for load, retries, backpressure, and disconnections.
Build infrastructure for red-team jobs, evaluation workloads, and model-serving services.
What we're looking forA systems engineer who reasons carefully about latency, failure.