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Technology Operational Risk Management (Technology Development) - Executive Director
senior · Risk & Compliance
Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities.
As an Executive Director Technology Development Risk Lead in Technology and Cybersecurity Operational Risk Management, you form an independent view of whether the controls over software delivery still hold now that a large share of code is written by artificial intelligence agents. You will use data-first approaches to show what is actually happening across the engineering estate, challenge the first line on what that data reveals, and report a position that senior management and regulators can rely on. You will do this as an individual contributor, close enough to the technology to stay credible with the engineers you challenge.
Your role offers the opportunity to join the Tech and Cyber Operational Risk Management team, responsible for the successful implementation and execution of the Compliance, Conduct, and Operational Risk framework within JPMorgan. You will provide Second Line of Defense challenge and oversight to our technology and cybersecurity partners. We are looking for someone who has built software and can hold their own with the engineers they challenge, and who will raise the analytical bar of the people around them without managing them.
Job Responsibilities:
Perform independent risk assessments of the controls governing how software is planned, written, reviewed, tested, and released, using data-first approaches and advanced analytics.
Challenge the first line on the control model applied to artificial intelligence coding assistants and agentic development tooling, covering human review of generated code, attribution of authorship, and the audit trail behind every change.
Evaluate the entitlements and credentials granted to development tooling and autonomous agents, and whether access controls still hold when a machine rather than a person initiates a change.
Assess whether observability and telemetry across the engineering estate is sufficient to detect data loss, misuse, and unexpected agent behaviour.
Utilize Python and SQL to analyze large engineering data sets, and build dashboards and reports that make development risk visible to senior management.
Define and test statistical hypotheses to identify thematic risks in software delivery from key risk indicator and key performance indicator performance.
Develop and maintain the annual oversight plan for this domain, and report an independent view to senior management, control committees, internal audit, and regulators.
Assess the prioritization and treatment of control findings, and monitor first line remediation to closure.
Coach and develop junior data scientists and risk professionals, raising the analytical bar of the function.
Required Qualifications, Capabilities, and Skills:
Bachelor's degree in Computer Science, Computer Engineering, Information Security, or a related field, or equivalent experience.
15 years of experience in technology risk, technology audit, software engineering, or application security within financial services.
Hands-on software development experience in Python.
Experience querying and analyzing data in SQL.
Hands-on experience with the software delivery toolchain, including source control, continuous integration and delivery pipelines, and automated testing.
Experience assessing or testing technology controls such as change management, access management, or secure software development.
Experience with data visualization and reporting tools such as Tableau or AWS QuickSight.
Experience presenting technology risk findings to senior management.
Experience coaching or developing junior technical colleagues.
Preferred Qualifications, Capabilities, and Skills:
Hands-on experience with artificial intelligence coding assistants or agentic development tooling in a professional software delivery setting.
Experience with large language models, including prompt design and evaluation of model output.
Experience with observability and monitoring platforms such as Splunk, Datadog, or Dynatrace.
Experience with cloud platforms, container orchestration, or infrastructure as code.
A professional certification such as CISA, CISM, CISSP, or CRISC.