Description

Alice is seeking an experienced and detail-oriented GenAI Safety 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 ActiveFence teams.

Requirements

Must Have

• Proven background in red teaming, AI safety research, or Responsible AI operations.
• Demonstrated experience managing complex projects and teams in a technical or analytical environment.
• 5+ years of experience
• Strong understanding of adversarial testing methods and model evaluation.
• Excellent communication skills in English, both written and verbal.