Compliance - Ccor Risk Management Director - Executive Director

JPMorgan Chase JPMorgan Chase · Banking · LONDON, United Kingdom · Corporate Sector

This role provides second-line-of-defense (2LoD) independent oversight for JPMorgan Chase's Chief Data & Analytics Office (CDAO) Product and Platform organization, focusing on Data/AI platforms, model onboarding, and agentic systems. The Director will develop and execute review strategies across the AI technical supply chain, ensuring compliance with risk appetite and regulatory expectations. Responsibilities include assessing risks in data flows, integrations, access controls, logging/traceability, and data residency, challenging remediation efforts, and overseeing governance for GenAI and agentic systems.

What you'd actually do

  1. Provide strategic guidance and proactive 2LoD oversight through targeted assessments of CDAO Product & Platform governance, processes, and control environments across the data and AI portfolio.
  2. Apply technical architecture expertise to challenge how data/AI services are designed and consumed (e.g., APIs, managed services, model gateways, identity and access patterns, orchestration layers), with a focus on secure control points and end-to-end auditability.
  3. Drive first line accountability for defining and reporting meaningful KRIs and control evidence (e.g., logging/traceability, data residency adherence, third-party dependencies, exception trends), and challenge content, quality, and outcomes as needed.
  4. Serve as an independent challenger for third-party/SaaS and managed AI platforms, validating risk and control expectations for data sharing/egress, vendor usage constraints, and operational resilience.
  5. Oversee governance for GenAI and agentic systems (including tool-enabled assistants and external model integrations), ensuring proportionate guardrails, least-privilege access, human oversight where required, and defined stop/containment mechanisms.

Skills

Required

  • Significant relevant experience in data/AI product and platform delivery with strong control-by-design practices, or risk/governance oversight across data/AI and cloud with demonstrated independent challenge
  • Demonstrated ability to operate with credible challenge and strong governance discipline (e.g., driving first line ownership, reviewing evidence, documenting risk positions, and escalating issues to resolution), while collaborating effectively with senior stakeholders and partners.
  • Demonstrable technical architecture fluency, with experience assessing and challenging designs for data/AI platforms and integrations (APIs and managed services, security gateways, IAM/least privilege, logging/observability, data residency and egress controls).
  • Strong understanding of AI/LLM capabilities and risks across the lifecycle (model onboarding/ingestion, retrieval/RAG patterns, model serving) and associated control points (traceability, access, data handling), including assessing control design and operational effectiveness in fast-changing environments.
  • Experience with agentic AI architectures and tool-enabled assistants (e.g., overseeing “Claude Code”-style deployments), including guardrails, access boundaries, traceability, and human oversight appropriate to risk.
  • Strong analytical and issue-spotting capability to drive risk decisions.
  • Excellent communication and counseling skills (including client-facing experience), with ability to translate complex technical topics into clear risk positions, influence outcomes, prioritize across competing demands, and drive closure on remediation action

Nice to have

  • Awareness of evolving AI regulations and AI risk frameworks, with ability to translate them into practical governance, controls, and operating model requirements (e.g., EU AI Act, NIST AI RMF; familiarity with NIST/ISO is beneficial)
  • Experience in a regulated environment is preferred (including roles within major cloud/service providers supporting regulated customers).

What the JD emphasized

  • independent oversight
  • independent challenge
  • risk appetite
  • regulatory expectations
  • agentic systems
  • external AI services
  • technical architecture
  • logging/traceability
  • data residency
  • third-party risk
  • access/entitlements
  • human-in-the-loop safeguards
  • GenAI
  • agentic systems
  • tool-enabled assistants
  • external model integrations
  • guardrails
  • least-privilege access
  • human oversight
  • stop/containment mechanisms
  • AI regulations
  • AI risk frameworks
  • control-by-design practices
  • risk/governance oversight
  • credible challenge
  • strong governance discipline
  • AI/LLM capabilities and risks
  • model onboarding/ingestion
  • retrieval/RAG patterns
  • model serving
  • agentic AI architectures
  • tool-enabled assistants
  • guardrails
  • access boundaries
  • traceability
  • human oversight
  • regulated environment

Other signals

  • AI/ML governance
  • AI risk management
  • AI platform oversight
  • Agentic systems oversight
  • Third-party AI services