Accountabilities:

AI-Driven Security Architecture: Design, develop, and pilot an AI-powered offensive security platform using autonomous agents, LLMs, agentic frameworks, and orchestration pipelines to identify attack paths and assess applications, APIs, and cloud environments.

Continuous Security Testing: Plan and execute systematic offensive security assessments across global infrastructure, microservices architectures, containerized workloads, and Kubernetes clusters.

Security Ecosystem Integration: Integrate offensive security findings with vulnerability management systems, SIEM/SOAR platforms, cyber threat intelligence feeds, and defensive security workflows to enable continuous remediation and automated retesting.

Technical Documentation and Governance: Develop technical architecture documents, RFCs, agent protocols, security automation standards, sandboxing mechanisms, and containment boundaries to ensure safe and reliable autonomous testing.

End-to-End Project Delivery: Lead complex, cross-functional engineering initiatives from initial scoping and architecture through implementation and operational deployment.

Risk Assessment and Communication: Translate attack paths, exploitation proof-of-concepts, vulnerability data, and technical findings into clear business risks and actionable recommendations for engineering leadership and executive stakeholders.

Vulnerability Prioritization: Develop AI-powered processes to validate exploitability, assess compensating controls, prioritize remediation based on business exposure, and automatically retest vulnerabilities after fixes are deployed.

Incident Response: Provide advanced offensive security expertise during critical incidents, participate in red team and purple team reviews, and lead corrective engineering initiatives following post-incident assessments.

Security Leadership and Mentorship: Lead architecture reviews and threat modeling sessions, establish engineering standards, and mentor senior and mid-level security professionals.

Cross-Functional Collaboration: Work closely with product, infrastructure, engineering, defensive security, and threat intelligence teams to improve organizational resilience and security practices.

Requirements

Extensive experience as a Senior or Staff Offensive Security Engineer, Red Team Specialist, or Principal Penetration Tester.

Proven expertise conducting complex security assessments across web applications, APIs, distributed cloud environments, and internal networks.

Hands-on experience developing or architecting LLM-powered applications, autonomous AI agents, agentic workflows, tool calling, and AI sandboxing environments.

Strong knowledge of adversarial AI evaluation and the security implications of autonomous systems.

Deep practical expertise in cloud-native technologies, container runtimes, Kubernetes architecture, and major cloud platforms.

Experience assessing and securing Kubernetes environments, including RBAC, admission controllers, pod security standards, network policies, and service mesh architectures.

Solid software engineering and programming skills, with the ability to develop production-grade security tools, microservices, integrations, and custom AI agent capabilities.

Experience integrating offensive security findings into vulnerability management platforms such as Jira, DefectDojo, or custom risk aggregation systems.

Familiarity with SIEM platforms, security telemetry, and detection engineering workflows.

Demonstrated ability to lead complex initiatives across engineering, product, and infrastructure teams.

Strong business-oriented mindset, with the ability to assess technical vulnerabilities based on their potential impact on customer data, platform trust, revenue, and business operations.

Excellent written and verbal communication skills, including the ability to present technical strategies and security risks to senior leadership and non-technical stakeholders.

Experience writing and reviewing RFCs, establishing technical standards, conducting architecture reviews, and mentoring other engineers.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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