AI Control Manager - Senior Associate

JPMorganChase•Jersey City, NJ

11d

About The Position

As AI continues to transform Finance, strong governance and rigorous controls are essential to ensure innovation is implemented safely, responsibly, and in line with regulatory expectations. In this role, you will help strengthen the control environment by applying advanced testing, data analytics, and automation to proactively identify issues and support effective risk management. As a AI Control Manager Senior Associate within the Client Onboarding & Documentation (CO&D) team, you will be responsible for identifying and monitoring significant risks, ensuring compliance with operational policies, control procedures, and legal/regulatory requirements through data-driven testing and automation. You will play a key role in assessing, governing, and monitoring AI solutions deployed within CO&D, ensuring they operate within the firmwide AI policies and standards. You will also perform controls testing and drive effective strategic control testing techniques utilizing data and execute testing engagements of strategic importance to CO&D. You will work with large datasets and conduct data testing across the full database using automation & data analytical tools, as applicable. Additionally, you will provide management with sufficient information to identify potential control gaps, Business As Usual (BAU) Operational breaks in CO&D and monitor key operational risks and regulatory activities/concerns. You will collaborate with colleagues across CO&D controls team, other Data Analytics teams, lines of business, Corporate Functions, and Technology to develop advanced automation solutions to identify errors / issues proactively. This team's role within the organization is to uphold the highest standards of ethical conduct and operational compliance in alignment with the various policies, laws, rules, and regulations governing the line of Business (LOBs) and Corporate Functions.

Requirements

Bachelor’s degree in Finance, Business, Technology or a related field
Demonstrated understanding of AI/ML concepts, with the ability to evaluate AI systems from a Risk & Controls perspective
Self-motivated, proactive “go-getter” with a strong sense of ownership and ability to hit the ground running.
Strong stakeholder management skills, with confidence in leading and handling calls, driving discussions, and ensuring timely follow-ups.
Ability to manage multiple priorities and engage effectively with stakeholders across functions.
Ability to work with large volumes of data efficiently and analyze large sets of data to accurately identify trends, patterns of problems
Hands-on experience simplifying and streamlining processes using AI and automation tools, including practical application of Large Language Models (LLMs) in control testing, documentation quality checks, issue identification, and executive-ready summarization.

Nice To Haves

Minimum 7+ years of experience in risk management and financial services industry; domains could include KYC, AML compliance, financial crimes, operational risk, audit, credit risk, market risk, business process management, Client onboarding & Documentation
Exposure to AI model validation, or AI oversight functions within a financial services institution
Prior hands-on control testing experience (first line testing, second line oversight testing, or internal audit).
Hands on / extensive control testing experience will be an advantage
Good knowledge of control design and root cause analysis
Strong analytical, critical thinking and problem-solving skills
working knowledge of Alteryx, Power BI, Tableau, UI Path, Pega, Python, and Microsoft Applications is preferred.

Responsibilities

Conduct AI Risk Assessments on AI/ML solutions deployed within CO&D, ensuring risks are clearly documented, escalated where appropriate, and remediated in a timely manner.
Ensure all AI/ML solutions within CO&D are compliant within the firmwide AI Governance standards and policies
Execute control testing activities as an individual contributor across KYC / client onboarding processes (e.g., CDD/EDD documentation completeness, evidence standards, adherence to procedures).
Perform proactive reviews as identified through regulatory, audit, or risk/control partner engagement.
Document testing scope, sampling approach, results, supporting evidence, and conclusions in a clear and audit-ready manner.
Identify control gaps, operational breaks, and recurring themes; support root cause discussions and remediation tracking with stakeholders.
Partner with Business, Operations, Control Managers, and other stakeholders to communicate results, trends, systemic issues, and control weaknesses through appropriate reporting.
Lead hands-on initiatives to simplify and streamline KYC/client onboarding control testing and documentation processes using AI-enabled tools (including LLM-based solutions), focusing on reducing manual effort, improving accuracy, and accelerating turnaround times.
Translate control testing requirements into effective prompt engineering and reusable prompt templates (e.g., for evidence checks, policy/procedure adherence validation, issue summarization), and iterate prompts based on testing outcomes and stakeholder feedback.
Identify and implement opportunities to embed AI into BAU controls monitoring to proactively surface operational breaks, recurring themes, and control gaps, with appropriate governance and audit-ready documentation.
Determine and share ideas on automation opportunities and actively contribute to the continuous learning mindset of the organization by bringing in new ideas.