Sr Director of Software Engineering - AI Governance

Shape how AI is governed, engineered, and scaled across JPMorganChase.

This role sits at the intersection of policy, controls, and automation, turning responsible AI requirements into repeatable, auditable, and highly automated AI workflows.

As a Senior Director of Software Engineering at JPMorganChase within the Chief Data and Analytics Office (CDAO), you will set and lead the AI governance framework enabling responsible adoption of AI/ML and generative AI at scale.

You will partner with Risk, Legal, Compliance, Controls, and Technology to translate policy into enforceable processes, control designs, and scalable platforms, embedding governance directly into MDLC/SDLC via automation, evidence capture, and continuous reporting.

You will drive executive transparency and ensure sustained readiness for audits, regulatory examinations, and client due diligence.

Job responsibilities



* Define and drive adoption of the in-business analytics ownership operating model, including roles, responsibilities, RACI/decision rights, and escalation paths across stakeholders.


* Own and continuously improve AI/ML governance artifacts (procedures, charters, operating models, job aids), including versioning, periodic reviews, and controlled refresh cycles.


* Partner with data science, architecture, engineering, and data teams to assess impacts of new policies/standards and convert requirements into actionable implementation plans, technical controls, and rollout playbooks.


* Lead end-to-end execution of CDAO and firmwide AI governance rollout plans, including communications, milestones, dependencies, adoption KPIs, and exception management.


* Design and build executive-ready governance platforms and reporting that provide real-time visibility into adherence, risk themes, control effectiveness, and remediation progress (with defensible audit trails and evidence-on-demand).


* Advance governance automation through agentic workflow orchestration and SDLC/MDLC integration to minimize manual intervention and increase standardization, repeatability, and traceability.


* Partner with Controls Management to identify, document, and monitor AI/ML risks, issues, and actions through established governance forums, including remediation tracking and control attestations.


* Define and execute the strategic roadmap for AI governance tooling and systems by standardizing processes and embedding governance-as-code patterns (e.g., automated gates, policy checks, and evidence capture) into delivery pipelines.


* Facilitate working sessions and stakeholder forums to drive alignment, resolve blockers, and promote consistent best practices across lines of business; serve as a senior interface to executives to drive decisions across competing objectives.


* Sets and scales multi-department strategy for agentic AI-enabled engineering and SDLC/TLM automation (using enterprise-authorized tools within the work environment) to drive firmwide obje...