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# AI Security Engineer

- **Company:** Olix
- **Location:** United Kingdom
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Cloud Computing Security, Information Leak Prevention, Python (Programming Language), Security Information and Event Management, Software Engineering, Data Streaming, TypeScript, AI Infrastructure, Okta, Large Language Models, Software Security, AI Coding Agents, Machine Learning Operations
- **Published:** November 5, 2026
- **Apply:** https://startup.jobs/ai-security-engineer-olix-10671739

## About the Role

* 5 or more years in security engineering, application security or cloud security, with at least 2 years securing AI or ML systems, LLM applications or agents.
 * Hands-on knowledge of LLM-specific threats and their mitigations.
 * Experience securing agentic systems: tool permissions, MCP servers, credentials and human approval steps.
 * AWS security experience and identity experience, ideally Okta.
 * Software engineering in Python or TypeScript.
 * Daily use of AI coding tools and agents in your own work.
 * Nice to have: experience with ISO 42001 or the NIST AI Risk Management Framework, or in a hardware or deep-tech company.

## Description

We build infrastructure for frontier AI, and we use AI to build it. Every team at OLIX works with AI tools, coding harnesses, models and agents, and we intend to use them more. We are hiring an AI Security Engineer to make that adoption safe without slowing it down.

You will map our AI footprint, secure our agents and their identities, protect our compute infrastructure, and build the controls that stop our IP and data leaving through AI systems. You will give teams a fast path to adopt new tools and make AI security measurable. This is a hands-on, high-ownership role with the freedom to define AI security at OLIX from the ground up.

Responsibilities

 * Map the AI footprint: build and maintain the inventory of AI tools, models, agents and data flows across the company.
 * Secure agents: give every agent a managed identity, least-privilege access, logged actions and the right human approvals.
 * Build controls against AI threats: prompt injection, data leakage, model and package supply chain, unsafe agent actions and shadow AI.
 * Secure AI infrastructure: harden the cloud compute our teams use to build and run AI workloads.
 * Make AI security measurable: run our ISO 42001 self-assessment and feed AI security events into our SIEM.
 * Enable safe adoption: review new AI tools within days and publish the guardrails teams need.