• Collaborate with business stakeholders to identify opportunities where AI agents can improve efficiency, accuracy, and customer experience. • Gather, analyze, and document functional and non-functional requirements for AI agent use cases. • Translate business workflows and policies into AI agent logic, decision trees, prompts, and automation rules. • Analyze AI agent performance using qualitative feedback and quantitative metrics (e.g., accuracy, resolution rates, escalation rates, latency). • Monitor AI agent behavior to identify gaps, bias, errors, or unintended outcomes and recommend corrective actions. • Partner with engineering and data science teams to support AI agent development, testing, deployment, and iteration. • Define success metrics, KPIs, and reporting dashboards for AI agent effectiveness and business impact. • Ensure AI agents comply with regulatory, risk, and responsible gaming requirements. • Support UAT, validation, and post-launch monitoring of AI agent releases. • Document AI agent workflows, decision logic, escalation paths, and operational guidelines. • Work closely with Customer Operations, Fraud, Risk, and Compliance teams to align AI behavior with real-world processes. • Facilitate feedback loops between end users and technical teams to drive continuous improvement. • Stay current on emerging AI, automation, and agent-based technologies and recommend enhancements. • Proactively identify optimization opportunities to expand AI agent capabilities across the organization.