Operates effectively across complex cross-functional environments, balancing customer, business, operational, policy, and technical considerations. Partner with Engineering, Data Science, Operations, Policy, and Risk teams to identify opportunities where AI, automation, and agentic systems can improve Trust & Safety outcomes. Design, build, and scale agentic workflows, Copilot experiences, automation solutions, and intelligent operational tools that increase team effectiveness and reduce manual effort. Identify repetitive, high-friction operational processes and transform them into automation-first solutions using AI-powered capabilities. Drive the end-to-end lifecycle of AI-enabled solutions, from problem definition and experimentation through deployment, adoption, and continuous improvement. Develop and maintain a deep understanding of emerging AI technologies, agent frameworks, Large Language Models (LLMs), and workflow orchestration patterns, identifying opportunities to apply them to Trust & Safety challenges. Partner with operational teams to design human-in-the-loop systems that balance automation efficiency with quality, safety, and accountability. Perform hands-on labelling, content review, evaluation, and adjudication activities as needed to establish ground truth, validate evaluation methodologies, calibrate quality standards, and improve model performance. Define success metrics and evaluation frameworks to measure the effectiveness, reliability, quality, and business impact of AI-driven solutions. Generate insights from operational data, workflow telemetry, experimentation results, and user feedback to continuously improve agent performance and automation outcomes. Build prototypes, proofs-of-concept, and lightweight solutions to rapidly validate ideas and accelerate learning. Drive cross-functional initiatives from problem identification through execution, balancing customer needs, operational requirements, technical feasibility, and business objectives. Communicate technical concepts, recommendations, and outcomes to both technical and non-technical stakeholders. Bachelor's Degree in Business, Operations, Economics, Analytics, Data Science, Computer Science, Information Systems, Engineering, a related field, or equivalent practical experience. 3+ years of experience in Product Management, Program Management, AI Solutions, Automation, Trust & Safety, Operations, Analytics, Risk Management, Fraud Prevention, Marketplace Integrity, or related domains. Experience identifying business or operational challenges and driving improvements through automation, process optimization, analytics, or technology-enabled solutions. Strong analytical and problem-solving skills, with experience leveraging data to prioritize opportunities, measure outcomes, and drive decision making. Experience working across cross-functional teams, including Engineering, Data Science, Operations, Product, and Business stakeholders. Demonstrated ability to translate ambiguous problems into scalable solutions that deliver measurable customer or business impact. Familiarity with Generative AI, Large Language Models (LLMs), AI-assisted workflows, agentic systems, workflow orchestration concepts, or related technologies. Experience evaluating solutions through experimentation, metrics, user feedback, or operational performance indicators. Strong communication, stakeholder management, and influencing skills, with the ability to drive alignment across diverse teams. Experience building, deploying, or scaling AI-powered workflows, intelligent assistants, automation platforms, agents, or workflow orchestration systems. Experience applying Generative AI, Large Language Models (LLMs), prompt engineering, retrieval-augmented generation (RAG), workflow automation, or agentic frameworks to real-world business problems. Working knowledge of Python, SQL, Power BI, Power Platform, Azure AI services, or similar analytics and automation technologies. Experience prototyping solutions, building proofs of concept, or rapidly validating ideas through experimentation and iterative development. Experience designing evaluation methodologies, feedback loops, telemetry frameworks, or quality measurement systems for AI-powered products and workflows. Experience partnering with Engineering and Data Science teams to improve AI systems through experimentation, user feedback, analytics, and continuous improvement. Experience working in Trust & Safety, Marketplace Integrity, Fraud Prevention, Risk Management, Compliance, Operations, or related domains. Demonstrated builder mindset with a track record of transforming manual workflows into scalable, automation-first solutions. Proven ability to thrive in fast-paced, ambiguous environments while driving measurable customer and business impact through innovation and continuous learning.
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