Senior Application Security Engineer – AI

. Provide implementation advice on securing AI-powered applications using frameworks such as OWASP ASVS and the OWASP Top 10 for LLM Applications .

Posted 9/22/2026full-timeLondon • United KingdomSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in securing AI-powered applications and managing security testing workflows, with a strong foundation in coding and cloud infrastructure. Capable of leading technical discussions and mentoring teams while implementing security best practices across various platforms.

Highest-signal resume keywords

Python ProgrammingTypeScript ProgrammingTerraform DevelopmentCloud Security Posture ManagementAI Application Security

ATS Keywords

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Hard Skills

Security TestingThreat ModellingPrompt Injection MitigationContainer SecurityKubernetes ManagementSCA ImplementationSAST ImplementationDAST ImplementationAutomated Infrastructure DevelopmentAgentic Development

Soft Skills

Outstanding Communication SkillsMentoringCollaborationTechnical DocumentationKnowledge Sharing

Tools & Technologies

Google Cloud PlatformAzureAWSGitHub ActionsDocker

Industry Keywords

OWASP ASVSOWASP Top 10AI-Specific FrameworksAgile DevelopmentSecurity Champions Network

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKotlinKubernetesPythonSDLCTerraformTypeScript

About the role

Key responsibilities & impact

Provide implementation advice on securing AI-powered applications using frameworks such as OWASP ASVS and the OWASP Top 10 for LLM Applications
Lead threat-modelling sessions for AI and agentic systems using STRIDE and AI-specific frameworks
Establish secure guardrails, allowlists, telemetry, and safe-by-default configurations for developer AI tooling
Manage SDLC security testing workflows for standard and AI-specific risks, including prompt injection and data leakage
Coordinate penetration tests, vulnerability triage, and cloud security posture management across GCP and Azure
Automate security tasks by contributing code to cloud infrastructure and security tooling
Facilitate the Security Champions network and organize security discussions
Deliver AI tooling safety training
Share expertise, document processes, and mentor engineering team members
Provide architectural feedback and lead technical security discussions

Requirements

What you’ll need

Strong ability to write and review code, preferably in Python, TypeScript, Kotlin and Terraform
Background in software development, SRE, DevOps, or practical security engineering
In-depth understanding of securing AI/LLM applications, agentic tooling, and developer AI tools
Knowledge of prompt injection mitigation, model integration risks, guardrails, telemetry, and frontier models via APIs or locally
Practical experience with agentic development using coding harnesses
Solid knowledge of major public cloud providers, preferably Google Cloud Platform; Azure or AWS beneficial
Knowledge of network infrastructure
Understanding of Kubernetes, Docker, and container security
Experience implementing and managing SCA, SAST, and DAST security testing programs in GitHub Actions pipelines
Experience with release packaging and artifact management
Capability to develop secure, automated infrastructure using Terraform
Interest in both offensive and defensive security
Ability to work collaboratively in enterprise-wide agile development environments
Outstanding written and verbal communication skills
Ability to explain complex vulnerabilities to technical teams and business stakeholders
Ability to share knowledge and mentor colleagues

Benefits

Comp & perks

Highly competitive remuneration and benefits package
Remuneration and benefits package kept under constant review
Recognition and rewards for extraordinary team or individual effort