Policy Deployment Lead, GenAI and Emerging Products

Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.

As a Policy Deployment Lead for GenAI Safety and Emerging Products within Trust & Safety, you will work at the intersection of technology and policy to enable innovation while protecting users. You will:

• Shape safety-by-design solutions for AI-powered and other emerging products and features.
• Build scalable safety and governance frameworks for emerging AI-powered products and technologies across multiple modalities, including text, image, audio, video, and multimodal systems.
• Partner closely with Product, Engineering, Data Science, User Research, Operations, Legal, Public Policy, and other cross-functional stakeholders to design and launch safe and compliant products. This role supports fast-moving and often ambiguous product areas, including new product launches and emerging technologies. The ideal candidate is comfortable balancing user safety, business priorities, regulatory expectations, and product innovation in a dynamic environment.

What will I be doing?

• Drive the development, deployment, and operationalization of scalable policy frameworks, governance systems, and moderation workflows across GenAI products and business lines.
• Partner cross-functionally with Product, Engineering, Ops, QA, and AI/ML teams to implement policy changes, evaluation frameworks, moderation strategies, and operational quality systems across downstream stakeholders and workflows.
• Support the development and scaling of GenAI evaluation and policy infrastructure capabilities, including benchmarking systems, evaluation datasets, golden set strategies, prompt governance workflows, auto-evaluation systems, and policy-ground-truth generation pipelines.
• Build and maintain structured operational feedback loops, quality review processes, calibration systems, and policy change management workflows to improve enforcement consistency, moderation quality, and operational scalability.
• Translate complex policy and safety requirements into actionable operational guidance, training materials, evaluation methodologies, and scalable implementation processes across multiple products and modalities.
• Surface operational gaps, enforcement inconsistencies, and post-deployment issues through data analysis, root cause analysis, and stakeholder feedback, and partner cross-functionally to drive continuous improvement of policy systems and workflows.
• Support organizational scalability through development of foundational operational assets and governance mechanisms, including SOPs, case banks, policy documentation, rollout frameworks, certification programs, and internal tooling processes.

Qualifications Minimum Qualification(s)

• 5+ years of experience in Trust & Safety, content policy, operations policy, governance, program management, or related operational strategy roles.
• Strong understanding of content moderation systems, policy interpretation, enforcement workflows, and operational quality management.
• Experience working cross-functionally with Product, Engineering, Operations, Data Science, AI/ML, QA, or related stakeholder teams.
• Proven ability to translate ambiguous policy or operational problems into scalable frameworks, processes, and operational solutions.
• Strong analytical reasoning, execution, and project management skills, with the ability to navigate ambiguity and balance multiple trade-offs.
• Excellent oral and written communication skills, with the ability to translate complex challenges into clear, persuasive language for cross-functional stakeholders at different levels.
• Adaptability and sound judgment, with a willingness to evolve your approach based on new information, user feedback, product changes, or market developments.

Preferred Qualification(s)

• Experience in GenAI safety, AI governance, model evaluation, policy deployment, or AI moderation systems.
• Familiarity with evaluation methodologies, benchmarking systems, golden sets, auto-labeling systems, or policy-labeled datasets.
• Experience designing or operationalizing training, calibration, certification, or quality assurance programs at scale.
• Familiarity with multimodal AI systems, prompt engineering, synthetic data generation, or human-in-the-loop evaluation workflows.
• Strong judgment in balancing policy consistency, operational practicality, scalability, and product needs across global products and markets.