We are seeking an experienced and detail-oriented Red Teaming team lead to oversee complex research and delivery efforts focused on identifying and mitigating risks in Generative AI systems. In this role, you will lead a multidisciplinary team conducting adversarial testing, risk evaluations, and data -driven analyses that strengthen AI model safety and integrity. You will be responsible for ensuring high-quality project delivery, from methodology design and execution to client communication and final approval of deliverables. This position combines hands-on red teaming expertise with operational leadership, strategic thinking, and client-facing collaboration. Key Responsibilities Operational and Quality Leadership
* Oversee the production of datasets, reports, and analyses related to AI safety and red teaming activities.
* Review and approve deliverables to ensure they meet quality, methodological, and ethical standards.
* Deliver final outputs to clients following approval and provide actionable insights that address key risks and vulnerabilities.
* Offer ongoing structured feedback on the quality of deliverables and the efficiency of team workflows, driving continuous improvement. Methodology and Research Development
* Design and refine red teaming methodologies for new Responsible AI projects.
* Guide the development of adversarial testing strategies that target potential weaknesses in models across text, image, and multimodal systems.
* Support research initiatives aimed at identifying and mitigating emerging risks in Generative AI applications. Client Engagement and Collaboration
* Attend client meetings to address broader methodological or operational questions.
* Represent the red teaming function in cross-departmental collaboration with other teams.
About us:
We are the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, we empower security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, we enable organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes
* Oversee the production of datasets, reports, and analyses related to AI safety and red teaming activities.
* Review and approve deliverables to ensure they meet quality, methodological, and ethical standards.
* Deliver final outputs to clients following approval and provide actionable insights that address key risks and vulnerabilities.
* Offer ongoing structured feedback on the quality of deliverables and the efficiency of team workflows, driving continuous improvement. Methodology and Research Development
* Design and refine red teaming methodologies for new Responsible AI projects.
* Guide the development of adversarial testing strategies that target potential weaknesses in models across text, image, and multimodal systems.
* Support research initiatives aimed at identifying and mitigating emerging risks in Generative AI applications. Client Engagement and Collaboration
* Attend client meetings to address broader methodological or operational questions.
* Represent the red teaming function in cross-departmental collaboration with other teams.
About us:
We are the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, we empower security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, we enable organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes
Requirements:
Must Have Proven background in red teaming, AI safety research, or Responsible AI Operations.
* Demonstrated experience managing complex projects or teams in a technical or analytical environment.
* Strong understanding of adversarial testing methods and model evaluation.
* Excellent communication skills in English, both written and verbal.
* Exceptional organizational ability and attention to detail, with experience balancing multiple priorities.
* Confidence in client-facing environments, including presenting deliverables and addressing high-level questions. Nice to Have
* Advanced academic or research background in AI, computational social science, or information integrity.
* Experience authoring or co-authoring publications, white papers, or reports in the fields of AI Safety, Responsible AI, or AI Ethics.
* Engagement in professional or academic communities related to Responsible AI, trust and safety, or Machine Learning security.
* Participation in industry or academic conferences.
* Familiarity with developing or reviewing evaluation frameworks, benchmarking tools, or adversarial datasets for model safety testing.
Must Have Proven background in red teaming, AI safety research, or Responsible AI Operations.
* Demonstrated experience managing complex projects or teams in a technical or analytical environment.
* Strong understanding of adversarial testing methods and model evaluation.
* Excellent communication skills in English, both written and verbal.
* Exceptional organizational ability and attention to detail, with experience balancing multiple priorities.
* Confidence in client-facing environments, including presenting deliverables and addressing high-level questions. Nice to Have
* Advanced academic or research background in AI, computational social science, or information integrity.
* Experience authoring or co-authoring publications, white papers, or reports in the fields of AI Safety, Responsible AI, or AI Ethics.
* Engagement in professional or academic communities related to Responsible AI, trust and safety, or Machine Learning security.
* Participation in industry or academic conferences.
* Familiarity with developing or reviewing evaluation frameworks, benchmarking tools, or adversarial datasets for model safety testing.
This position is open to all candidates.
