We are hiring a senior Product Owner to lead the design, delivery, and scale‑out of agent‑based automation across core financial services operations. This role sits within the Global Delivery Simplification organization and focuseson re‑imagininghow complex operational processes are executed using agentic AI in a regulated, control‑intensive environment.

The Product Owner will ensure solutions deliver measurable reductions in manual exception handling, aged breaks, cycle time, operational risk, and unnecessary handoffs, while improving transparency, control effectiveness, and client outcomes. This includes meeting regulatory, audit, data governance, and model risk expectations by embedding explainability, evidence capture, human-in-the-loop review, and escalation controls into the product design.

This is a hands-on product leadership role requiring strong judgment, deep partnership with operations, technology, risk, data, and control teams, and accountability for outcomes beyond initial delivery, including adoption, sustained performance, exception reduction, and value realization in live operations.

ROLE PURPOSE

The Product Owner leads a cross-functional POD responsible for conceiving, delivering, and scaling agentic capabilities across core business services including Fund Accounting, Middle Office, Transfer Agency, and Custody.

The role is accountable for product strategy, roadmap, prioritization, and value delivery for agent-based exception management, including exception intake, classification, root-cause analysis, recommended resolution, automated remediation where appropriate, and controlled escalation to human reviewers.

Success in this role requires the ability to balance automation ambition with operational materiality and risk. The Product Owner must ensure that controls, auditability, explainability, evidence capture, approval logic, and escalation thresholds are treated as core product features, not downstream compliance activities.

KEY RESPONSIBILITIES

•Own end‑to‑end business outcomes for agent‑based solutions, including efficiency gains, capacity release, quality improvement, risk reduction, and client experience uplift

•Define and communicate a clear product vision for how agentic AI will transform exception management across operational domains, from detection and triage through investigation, resolution, escalation, and post-resolution learning.

• Identify and prioritize opportunities where agent‑based automation can materially improve accuracy, cycle time, resilience, and control effectiveness.
• Align product strategy with business outcomes, regulatory expectations, and enterprise AI risk frameworks.
• Translate simplification goals into clear product hypotheses, roadmaps, and measurable success criteria.
• Act as the voice of the business, converting domain and operational requirements into a prioritized backlog of product increments and user stories.
• Lead agile execution with a focus on incremental value delivery, rapid learning, and operational readiness.
• Oversee the full lifecycle of agentic AI solutions, including problem framing, data grounding, workflow integration, approval and human‑in‑the‑loop design, evaluation, production rollout, and post‑deployment performance management.
• Treat controls, auditability, explainability, and evidence capture as core product features, not downstream compliance activities.
• Use domain expertise to define materiality thresholds, escalation paths, and failure modes appropriate for autonomous or semi‑autonomous execution.
• Make informed build, defer, or stop decisions based on agent performance, operational materiality, and control outcomes.
• Own ongoing agent performance management in production, including accuracy trends, exception patterns, drift indicators, and remediation actions.
• Partner closely with operations leaders, SMEs, risk, data, and engineering teams to validate acceptance criteria and business readiness.
• Define and track KPIs tied to efficiency, quality, cycle time, client outcomes, and risk reduction; quantify and communicate value delivered.
• Communicate progress, risks, and outcomes clearly to senior stakeholders and influence alignment across global teams.

SKILLS AND CAPABILITIES
• Strong product management capability, including product strategy, roadmap definition, backlog prioritization, and stakeholder management.
• Strong product judgment, with the ability to balance automation ambition, operational risk, regulatory expectations, and user trust.
• Proven experience leading cross‑functional agile PODs in complex environments.
• Excellent communication and influencing skills, with comfort engaging both technical and non‑technical audiences.
• Deep understanding of one or more business areas: Fund Accounting, Middle Office, Transfer Agency, or Custody (or demonstrated ability to learn quickly and operate credibly with SMEs)
• Understanding of prompt engineering and model‑alignment practices to improve accuracy and reduce risks such as hallucinations, bias, and data leakage.
• Ability to interpret agent telemetry and operational signals such as low‑confidence outputs, anomalies, repeated failure patterns, and exception spikes.
• Exposure to agent evaluation approaches, including testing edge cases and adversarial scenarios to validate agent behavior.
• Understanding of monitoring and escalation patterns for AI agents, including when outputs should be suppressed, flagged, or routed to human reviewers.
• Solid understanding of data governance principles including data quality, lineage, metadata, and stewardship.

EXPERIENCE REQUIREMENTS

• 7+ years owning products or platforms in complex, regulated operational environments, with clear accountability for outcomes rather than only delivery.
• Experience in global financial services operations, preferably in Fund Accounting, Middle Office, Transfer Agency, or Custody.
• Exposure to AI, automation, or digital transformation programs in enterprise environments.
• Prior experience working closely with engineering, data, risk, compliance, and audit functions.
• Experience launching and scaling solutions into live operations, not just pilots or proofs of concept.
• Experience working in agile POD or product‑centric delivery models.