AGENTIC AI Testing Manager, Global Delivery Simplification, Managing Director

Who we are looking for We are hiring a Managing Director to define and lead the enterprise testing strategy and governance framework for the agentic AI platforms across global financial services operations. This role sits within the Global Delivery Simplification organization and is accountable for ensuring that agent-based systems are safely deployed, rigorously validated, and continuously monitored in production, with full alignment to enterprise risk, governance, and regulatory expectations. This is a strategic leadership role, responsible for setting the vision, standards, and operating model for testing agentic AI systems in a control-intensive operational environment. Why this role is important to us The Managing Director will establish end-to-end testing strategy, governance, and control standards for agentic AI solutions, ensuring platforms and user cases deployed are fit-for-purpose, auditable, resilient, and enterprise-ready. The role owns the definition of testing frameworks across functional, non-functional, AI-specific, and risk-based validation dimensions, and ensures testing is embedded as a core control within the AI lifecycle. What you will be responsible for Define and own enterprise testing strategy for agentic AI platforms Design and establish AI-specific testing frameworks, covering agent reasoning validation, decision-making accuracy, edge-case and adversarial testing, model drift detection, and overall AI system reliability, robustness, and governance compliance. Set standards for testing coverage, acceptance criteria, and go-live readiness gates. Align testing strategy with enterprise AI, product, and data platform roadmaps. Establish testing governance models, including approval frameworks, escalation mechanisms, and sign-off protocols. Define and enforce control requirements for agentic systems, including human-in-the-loop validation, failure handling, and fallback mechanisms. Ensure testing frameworks meet regulatory, audit, model risk management, and data governance expectations. Define risk-based testing approaches based on materiality, business impact, and autonomy level of agents. Oversee validation of agent behavior, including accuracy, explainability, consistency, and operational safety. Ensure testing captures systemic risk patterns, bias, hallucination risks, and control gaps. Establish frameworks for continuous testing and monitoring post go-live, including drift detection and regression validation. Define and govern testing operating model across PODs, including roles, responsibilities, and accountability. Provide executive oversight of test execution across multiple agentic AI initiatives. Ensure consistency of testing standards across domains (FA, MO, TA, Custody). Drive adoption of tooling, automation, and test observability frameworks. Build and lead senior testing leadership team across regions. Partner with Product, Engineering, Data, Risk, and Operations leaders to ensure end-to-end delivery readiness. Represent testing in senior governance forums and regulatory discussions.

Ability to define and institutionalize testing strategies and operating models at enterprise scale Strong judgment in balancing innovation vs control, speed vs risk, automation vs assurance Deep understanding of agent-based system behavior, including reasoning flows, decision boundaries, and failure modes Strong grasp of AI-specific risks (hallucination, drift, bias, explainability) and how to design testing to mitigate them Expertise in designing control frameworks for AI-enabled systems, including human-in-the-loop, approval gates, and fallback logic Strong understanding of model risk management, audit expectations, and regulatory scrutiny Strong influencing capability across Product, Engineering, Risk, Compliance, and senior leadership Proven ability to build, scale, and lead multi-layer testing organizations Strong ability to define accountability models, governance forums, and escalation paths