Enterprise Security Engineer (AI & Enterprise Security)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Secure internal enterprise systems and AI/agentic workflows by defining secure SDLC standards, building reference architectures, and translating threat modeling findings into actionable controls and detection requirements. Partner with the CISO and business teams to raise security adoption, conduct technical security reviews, and evaluate emerging AI/ML security tools. Engineer and automate AI-first security workflows to help the security team scale across product security, SOC, and GRC.

Location: United Kingdom, Ireland

Workplace: Hybrid

Employment Type: Full time

Job Function: Cybersecurity

Key Responsibilities

•Develop secure SDLC standards for internal apps and AI workflows, including patterns, reference architectures, and documentation for self-serve teams.
•Conduct threat modeling, risk assessments, and technical security reviews for enterprise systems, internal apps, and AI/agentic deployments; prioritize risks and advise mitigations.
•Design safeguards for enterprise AI tooling, including agents and non-human identities, and evaluate/integrate emerging AI/ML security tools.
•Engineer and automate AI-first security workflows and tooling that helps the wider security team scale.
•Collaborate with business teams to raise the profile of security and adopt secure practices, especially for AI and low-code environments.

Key Requirements

•Hands-on software and enterprise security experience with strong security expertise.
•Proficiency in secure SDLC fundamentals, including threat modeling, secure design, vulnerability management, and CI/CD security.
•Comfortable writing and reviewing code (Python, Go, TypeScript, or similar) and using it to build security integrations/workflows.
•Experience with security tooling at scale such as SAST, DAST, SIEM, endpoint, cloud, identity, and vulnerability management platforms.
•Knowledge of AI/ML security risks, attack vectors, vulnerabilities, and familiarity with agentic AI/generative AI tool frameworks.

Skills:CommunicationInterpersonal skillsCollaborationSelf-starterOwnership

Tech Stack:PythonGoTypeScriptCI/CDThreat modelingSecure SDLCVulnerability managementSASTDASTSIEMEndpoint securityCloud securityIAMAI/ML securityAI toolingAgentic AI frameworksGenerative AIJenkins

Company Brief

Cloudbees

Website

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Cloudbees

2 months ago

Enterprise Security Engineer (AI & Enterprise Security)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: United Kingdom, Ireland

Workplace: Hybrid

Employment Type: Full time

Job Function: Cybersecurity

Key Responsibilities

•Develop secure SDLC standards for internal apps and AI workflows, including patterns, reference architectures, and documentation for self-serve teams.
•Conduct threat modeling, risk assessments, and technical security reviews for enterprise systems, internal apps, and AI/agentic deployments; prioritize risks and advise mitigations.
•Design safeguards for enterprise AI tooling, including agents and non-human identities, and evaluate/integrate emerging AI/ML security tools.
•Engineer and automate AI-first security workflows and tooling that helps the wider security team scale.
•Collaborate with business teams to raise the profile of security and adopt secure practices, especially for AI and low-code environments.

Key Requirements

•Hands-on software and enterprise security experience with strong security expertise.
•Proficiency in secure SDLC fundamentals, including threat modeling, secure design, vulnerability management, and CI/CD security.
•Comfortable writing and reviewing code (Python, Go, TypeScript, or similar) and using it to build security integrations/workflows.
•Experience with security tooling at scale such as SAST, DAST, SIEM, endpoint, cloud, identity, and vulnerability management platforms.
•Knowledge of AI/ML security risks, attack vectors, vulnerabilities, and familiarity with agentic AI/generative AI tool frameworks.

Skills:CommunicationInterpersonal skillsCollaborationSelf-starterOwnership

Tech Stack:PythonGoTypeScriptCI/CDThreat modelingSecure SDLCVulnerability managementSASTDASTSIEMEndpoint securityCloud securityIAMAI/ML securityAI toolingAgentic AI frameworksGenerative AIJenkins

Company Brief

Cloudbees

Website