An AI Penetration Tester carries out structured security assessments of products and platforms that include machine learning or generative AI components. The job applies the methods of traditional penetration testing, such as scoping, reconnaissance, exploitation and reporting, to systems where a model sits in the middle of the application and can be steered by user input.
Organisations hire AI penetration testers because AI features add attack paths that standard web and infrastructure tests miss. A chatbot with access to internal tools, a retrieval pipeline reading untrusted documents or a model registry with weak access controls can each expose data or functionality. Enterprise customers, insurers and auditors increasingly expect an independent test before an AI product goes live.
What does an AI Penetration Tester do?
Engagements are usually scoped and time-boxed. An AI Penetration Tester agrees rules of engagement, maps the system, tests the AI-specific attack surface alongside conventional controls, and delivers a report with findings ranked by risk. Some roles are in-house and test internal products continuously. Others sit in consultancies and test client systems.
- Mapping the architecture of AI applications, including model endpoints, orchestration layers, vector databases, plug-ins and connected tools
- Testing for prompt injection, insecure output handling and excessive agency, where a model can trigger actions it should not
- Checking authorisation boundaries so that retrieval and agent features cannot reach other tenants' or users' data
- Assessing model serving infrastructure, MLOps pipelines and model registries for exposed secrets, weak access control and insecure configuration
- Reviewing supply chain risk, such as unsafe deserialisation of model files and unverified third-party models or datasets
- Running conventional web, API and cloud tests around the AI components
- Writing clear reports with evidence, risk ratings and remediation advice, and retesting fixes
Key skills and backgrounds
Most AI penetration testers start as web application, API or cloud penetration testers and add AI expertise on top. That foundation is important because many serious findings in AI products are still classic issues, such as broken access control or server-side request forgery, reached through a new route. Hiring managers should check both halves. Ask about a conventional engagement and about an AI-specific finding, and listen for how the candidate scoped, exploited and reported each.
Recognised offensive security certifications show baseline competence, but evidence of AI testing through write-ups, tooling or past engagements is the stronger signal.
- Web application and API testing, including authentication, authorisation, injection and server-side request forgery
- Understanding of LLM application patterns, including retrieval-augmented generation, function calling and multi-agent orchestration
- Cloud security across major providers, containers and secrets management
- Knowledge of the OWASP guidance on LLM application risks and MITRE ATLAS techniques
- Scripting in Python for custom payloads and test automation
- Awareness of how ML pipelines, model formats and serving frameworks are built and where they are exposed
- Report writing for technical and non-technical readers, with honest risk ratings
Where AI Penetration Testers work
Security consultancies and penetration testing firms hire AI specialists to meet client demand for AI assessments. AI-first scale-ups and SaaS businesses adding AI features hire in-house testers or contractors before major releases. Banks, insurers, healthcare providers and public sector bodies hire them into internal offensive security teams as AI adoption spreads. Cloud and platform providers also employ AI penetration testers to assess their own model hosting and AI services.
AI Penetration Tester vs related roles
AI penetration testing shares techniques with research and red-team roles but differs in purpose and output.
- A Prompt Injection Researcher develops new injection and jailbreak techniques, while an AI Penetration Tester applies known techniques within a scoped assessment.
- An AI Offensive Security Researcher works on open-ended research into new attack classes, rather than testing a specific system against an agreed scope.
- An AI Vulnerability Researcher hunts for previously unknown flaws in AI software such as frameworks, inference servers and libraries, which often leads to coordinated disclosure.
Salary and market data
Rates for AI penetration testers depend on whether the role is permanent or contract, in-house or consulting, and how much AI-specific experience the candidate brings. Our GenAI and agentic systems salary guide sets out current ranges, the AI and deep tech salary guides cover adjacent roles, and the deep tech salary calculator lets you check an offer.
Hiring AI Penetration Testers with DeepRec
DeepRec recruits security specialists into GenAI and agentic systems teams across Europe and the US, working from London, Berlin, Zurich, Dublin and Boston. We screen AI penetration testers on both conventional and AI-specific testing, so you see candidates who can scope and report an engagement properly. We hire on a permanent, contract, retained and executive search basis, and contract testers are often a practical way to cover a pre-release assessment. To start, go to Looking to Hire.