Adversarial AI Research Engineer for AI Security
Opportunity Summary
You will work on an AI security team at the intersection of offensive security and artificial intelligence. The focus is mitigating risk across AI initiatives by creating novel security frameworks, specialized tooling, and foundational testing methodologies for generative and predictive systems. Responsibilities include leading efforts that produce adversarial datasets, designing in-house content generation systems, and supporting knowledge sharing across security and research partners. This is well-suited to engineers who enjoy rigorous evaluation, adversarial thinking, and building repeatable security research pipelines.
Ideal Candidate
An engineer with deep experience in AI security research or offensive methods applied to ML systems. You think in terms of test frameworks, measurable risk, and scalable tooling that improves coverage across multiple AI initiatives.
Project Insights
- Strong roles here often produce tooling that other teams can operationalize
- Expect collaboration across ethics, research, engineering, and security operations
- Evaluation rigor, including metrics and baselines, is a major differentiator
How to Prepare
- Bring 1 to 2 examples of adversarial AI work, including evaluation results or metrics
- Be ready to discuss how you validate that a security test is meaningful and not flaky
- Review common AI security categories like data poisoning, prompt injection, and model misuse
Typical Challenges
- Creating adversarial datasets that reveal real-world failure modes
- Designing repeatable evaluation pipelines for AI behaviors
- Balancing offensive research with safe, responsible disclosure and controls
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Project Details
Skills & Requirements
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