Compliance - Operational Risk Management - Vice President

JPMorganChase•Brooklyn, NY

About The Position

As an Operational Risk Management Lead – Vice President within JPMorgan Chase’s Compliance, Conduct and Operational Risk (CCOR) organization, you will provide independent oversight and assessment of the processes, risks, and controls supporting Consumer & Community Banking (CCB) Operations. You will help evidence sound operational risk management and regulatory compliance, operating under the CCOR Framework and partnering with cross-functional teams as a primary point of contact for operational risk and regulatory compliance matters. You will design and execute the CCOR program’s second-line responsibilities for managing compliance, conduct, and operational risk. This includes evaluating first-line control design and execution through risk and control assessments, analytics, deep-dive reviews, and governance and reporting practices. You will provide credible challenge and oversight of AI, including generative and agentic AI, advanced analytics, and automation used in CCB Operations. The role requires maintaining a risk-based oversight program across AI-enabled products and processes, assessing risks throughout the AI lifecycle, and challenging the effectiveness of related controls. You will review new products, material process changes, technology implementations, and emerging AI use cases early enough to help establish appropriate assessments, governance, controls, ownership, and evidence standards. You will work with business and functional partners to translate technical and risk topics into clear guidance for senior management, identify and escalate material risks and control deficiencies, and build collaborative relationships while maintaining second-line independence.

Requirements

At least 5 years of experience in operational risk, technology risk, compliance, controls, audit, model risk, or a related financial-services risk discipline.
Experience providing independent risk oversight or credible challenge of AI-enabled technologies, automation, advanced analytics, or technology-supported business processes.
Working knowledge of AI concepts, architectures, data dependencies, system integrations, and lifecycle practices, including how these technologies operate within end-to-end business processes.
Ability to identify and assess how AI applications may introduce or amplify operational, technology, data, model, compliance, conduct, privacy, third-party, resiliency, and customer-impact risks.
Experience evaluating governance and controls across the AI lifecycle, including intake, design, testing, validation, implementation, monitoring, change management, incident response, and decommissioning.
Knowledge of technology risk-management principles and controls, including data quality and lineage, access management, system development, change control, human oversight, output monitoring, incident management, and operational resilience.
Strong analytical and critical-thinking skills, including experience using data, metrics, incidents, exceptions, complaints, or testing results to identify trends, control weaknesses, and emerging risks.
Ability to translate complex technology and risk matters into clear, defensible recommendations for senior management and nontechnical stakeholders.
Ability to collaborate across Business, Technology, Data, Cybersecurity, Controls, Legal, Compliance, Model Risk, Privacy, and other risk disciplines while maintaining effective second-line independence.
Ability to learn quickly, manage multiple demands, and adapt to changing priorities.
Strong judgment, written and verbal communication, stakeholder management, and escalation skills, including the ability to manage multiple priorities in a rapidly evolving risk environment.
Self-starter able to own and drive deliverables while collaborating with a broader team, engage with all levels of the organization on risk and control matters, and escalate appropriately.

Nice To Haves

Experience in operational risk, compliance, controls, legal, or fraud risk within financial services.
Front-to-back operational knowledge of the relevant line of business, including its products, processes, and systems.
Track record of using AI tools for research and interpretation; designing and executing analyses; aggregating risks across processes and products; and translating findings into clear risk insights and actionable recommendations.
Advanced qualifications such as CRMP, ORM, PRM, CRCM, CAMS, CIA/CISA, or PMP.
Advanced degree such as a JD, MBA, or MS in Risk/Analytics.
Experience engaging regulators and internal audit.
Strong data fluency and proficiency in self-service analytics and data visualization tools to support CCOR oversight.
Ability to influence cross-functional partners and present to senior stakeholders.

Responsibilities

Provide independent, second-line CCOR oversight and credible challenge of AI, including generative and agentic AI, advanced analytics, and automation used in CCB Operations.
Maintain a risk-based oversight program for AI-enabled products, processes, decisioning, monitoring, customer interactions, and operational workflows in alignment with the CCOR Framework and applicable technology, data, model, and AI governance requirements.
Maintain sufficient technical understanding of evolving AI capabilities to evaluate how solutions function, use data, integrate with business processes, generate outputs or actions, and affect upstream and downstream activities.
Assess and monitor operational, technology, data, model, compliance, conduct, privacy, third-party, resiliency, and customer-impact risks introduced or amplified by AI adoption and change.
Evaluate AI use cases throughout their lifecycle, from intake and classification through design, development, testing and validation, approval, implementation, production monitoring, change management, incident response, and decommissioning.
Independently challenge the effectiveness of AI-related controls, including data quality and lineage, access management, testing and validation, explainability, human oversight, output validation, monitoring, change control, exceptions, recordkeeping, and escalation.
Review new products, material process changes, technology implementations, and emerging AI use cases early to ensure appropriate risk assessments, governance decisions, control requirements, accountable ownership, and evidence standards are established before deployment or expansion.
Verify AI applications operate within approved parameters and intended business purpose, with particular focus on unintended or unreliable outcomes, automation bias, inappropriate reliance, control circumvention, process degradation, and customer or employee impacts.
Partner with Business, Technology, Data, Cybersecurity, Controls, Legal, Compliance, Model Risk, Privacy, and other risk disciplines to translate technical matters into clear guidance for senior management.
Escalate material risks, control deficiencies, governance gaps, or unclear accountability.
Stay current on evolving operational risks and regulations; apply critical and analytical thinking in risk assessments; design and execute reviews; identify negative trends, control gaps, and emerging risks; and escalate issues promptly.
Engage senior management and build credible, trust-based, collaborative relationships across lines of defense and functional groups.