Adversarial AI Tester

The Adversarial AI Tester is responsible for evaluating, stress-testing, and validating artificial intelligence and machine learning systems against adversarial threats, misuse, bias, and failure modes. This role plays a critical part in ensuring the robustness, safety, reliability, and ethical performance of AI models across production and pre-production environments. This position is strictly limited to candidates who currently reside in the United States and are legally authorized to work in the U.S. Applications from individuals residing outside the United States will be rejected. Key Responsibilities: Design and execute adversarial testing strategies for AI and machine learning models Identify vulnerabilities related to model robustness, security, bias, hallucinations, and misuse Perform red-teaming, prompt injection testing, model evasion testing, and data poisoning simulations Develop test cases to evaluate AI behavior under malicious, edge-case, or unexpected inputs Document findings, risks, and mitigation recommendations in clear technical reports Collaborate with ML engineers, data scientists, and security teams to remediate identified weaknesses Validate fixes and improvements through regression and re-testing Support responsible AI, governance, and compliance initiatives Stay current on emerging adversarial AI techniques, threats, and industry best practices Required Qualifications: Bachelors degree in Computer Science, Artificial Intelligence, Cybersecurity, Data Science, or a related field 3–6 years of experience in AI/ML testing, model evaluation, security testing, or red team activities Strong understanding of machine learning concepts, including supervised and unsupervised models Experience testing large language models (LLMs), computer vision, or predictive systems Familiarity with adversarial attack techniques (e.g., prompt injection, model evasion, data poisoning) Proficiency in Python and common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) Strong analytical, documentation, and communication skills Ability to work independently in a fully remote environment Preferred Qualifications: Masters degree or Ph.D. in AI, Machine Learning, or Cybersecurity Experience with AI governance, model risk management, or responsible AI frameworks Familiarity with cloud-based AI platforms (AWS, Azure, GCP) Knowledge of NIST AI Risk Management Framework or similar standards Experience with security testing tools, red teaming methodologies, or AI audits Compensation: Annual Salary Range: $120,000 – $165,000 USD, based on experience, technical expertise, and geographic location Benefits: Comprehensive medical, dental, and vision insurance 401(k) retirement plan with employer matching Paid time off, paid holidays, and sick leave Life, short-term, and long-term disability insurance Flexible remote work schedule Professional development, research, and certification support Employee wellness and assistance programs Work Authorization & Residency Requirement: Must be legally authorized to work in the United States Must currently reside within the United States Applications from candidates outside the U.S. will not be considered