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Systems Engineer

refractal • United Kingdom
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Own the services and infrastructure that keep Refractal secure and reliable in production. Build and operate runtime enforcement, observability, evidence storage, streaming services, and cloud infrastructure. Requires strong backend/distributed systems experience, Python, Postgres, and production observability skills.

Key Highlights
Own services and infrastructure for production security and reliability
Build low-latency runtime enforcement and observability/tracing
Tamper-evident evidence storage and multi-tenant isolation
Reliable event/streaming services with backpressure handling
Cloud infrastructure, continuous delivery, secrets, and trust boundaries
Key Responsibilities
Build and operate a low-latency runtime enforcement pipeline with predictable failure behaviour
Own observability and tracing across agent actions, tool calls, model calls, and enforcement decisions
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
Own cloud infrastructure, continuous delivery, secrets, artefact verification, and production trust boundaries
Technical Skills Required
Python Postgres OpenTelemetry
Benefits & Perks
Meaningful equity
Performance-linked bonus
UK Skilled Worker visa sponsorship
Clear path to technical leadership

Job Description

About Refractal

Refractal is an AI security company building the infrastructure organisations need to defend against autonomous AI threats. 2026 has shown that generally capable intelligence is here. 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.S. Navy. 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.

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