Senior AI Security Engineer - Platform & Cloud

Quberesearchandtechnologies; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

QRT, a global quantitative and systematic investment manager, seeks a Staff Security Engineer to lead the AI Security function. You will design and implement security controls across inference gateways and developer tooling, embedding secure options by default and defining standards for AI deployment.

You will own secrets handling, telemetry, and threat modelling across platforms, with a focus on auditability, provenance, and secure workflows in a production environment.

Qualifications

• Eight or more years in security engineering or related technical discipline.
• Strong academic record in computer science or software engineering.
• Ability to build and ship controls in production systems, not just review them.
• Depth in security domains with breadth across others.
• Experience securing cloud platforms and CI/CD pipelines.
• Fluent day-to-day use of coding agents.

Responsibilities

• Design and implement security controls in inference gateways and tooling as code.
• Embed controls so secure options are the default across systems.
• Define standards and patterns for AI development and deployment.
• Secure developer harnesses, plugins, and provenance of models.
• Own secrets handling and vulnerability management across AI tooling.
• Threat model live systems across platform and AI supply chain.
• Drive secure defaults and governed identities with audit trails.

Skills

LLM platforms

Inference gateways

Agent frameworks

Security engineering

Cloud security

CI/CD security

Auditing and telemetry

Secure defaults

Decision making under uncertainty

Coding agents

Education

Computer science or software engineering degree

Tools

CI/CD pipelines

Cloud platforms

Job description

QRT, a global quantitative and systematic investment manager, seeks a Staff Security Engineer to lead the AI Security function. You will design and implement security controls across inference gateways and developer tooling, embedding secure options by default and defining standards for AI deployment.

You will own secrets handling, telemetry, and threat modelling across platforms, with a focus on auditability, provenance, and secure workflows in a production environment.