Job Description
Title: AI Security Penetration Tester / AI Red Team Engineer
Position Overview
We are seeking a highly skilled AI Security Penetration Tester / AI Red Team Engineer to lead offensive security engagements focused on AI/ML-powered applications and platforms. This role is responsible for identifying, exploiting, and demonstrating security risks across traditional and AI-specific attack surfaces, including LLMs, AI-enabled APIs, and AI-driven business logic.
- You will collaborate with Engineering, Security, Red Teams, SOC, and AI research teams to proactively identify weaknesses, simulate real-world AI attacks, and guide remediation strategies to strengthen enterprise AI security posture.Key Responsibilities
- Conduct AI-focused penetration testing across web, API, mobile, and AI-powered systems.
- Perform AI red teaming exercises including prompt injection, jailbreak testing, model evasion, and adversarial ML attacks.
- Identify risks such as model poisoning, data leakage, adversarial inputs, and AI business logic abuse.
- Perform threat modeling and architecture reviews for AI-enabled applications.
- Develop and enhance AI-focused offensive security tools and testing methodologies.
- Research emerging AI attack techniques and assess potential business impact.
- Deliver comprehensive penetration testing reports and executive-ready presentations.
- Lead engagements end-to-end including scoping, execution, reporting, and remediation validation.
- Partner with engineering teams to provide actionable security recommendations.
- Collaborate with Red Teams and SOC to continuously improve AI security playbooks.
- Required Qualifications
- 3+ years of hands-on penetration testing experience (web, API, mobile).
- Demonstrated experience in AI red teaming, LLM security testing, or adversarial ML.
- Proficiency with tools such as Burp Suite Pro, Netsparker, Checkmarx, or similar.
- Working knowledge of AI/ML frameworks (TensorFlow, PyTorch, LLM APIs, LangChain).
- Strong understanding of OWASP Top 10, API security, and modern attack vectors.
- Excellent written and verbal communication skills.
- Relevant security certifications (GWAPT, OSWE, OSWA, CREST, etc.) preferred.
- Bachelor’s degree in Computer Science, Cybersecurity, or equivalent experience.
- Preferred Qualifications
- Experience testing LLM-based applications, chatbots, copilots, or AI workflows.
- Familiarity with MLOps, model deployment security, and cloud AI platforms (AWS, Azure, Google Cloud Platform).
- Ability to build custom offensive tools/scripts in Python, Go, or similar languages.
- Exposure to SOC operations, detection engineering, or purple team exercises.
- Contributions to AI security research, blogs, talks, or open-source projects.
- What Success Looks Like
- AI vulnerabilities identified before production release
- Clear demonstration of AI attack paths and business risk
- Actionable remediation guidance adopted by engineering teams
- Continuous evolution of AI red teaming methodologies
- Measurable improvement in AI security posture
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