Director, Head of Engineering – Model Risk Management

Role Summary: The Director, Head of Engineering – Model Risk Management will be a member of the Engineering Practice and aligned to the Risk & Compliance Hub. This role is responsible for engineering strategy, architecture, and delivery for the Model Risk Management domain, with a focus on scalable platforms, strong controls, agile execution, and an AI-first approach to engineering outcomes.

Key Responsibilities

Design architectures to support model risk management, model validation, and ongoing monitoring processes.

Codify and automate quantitative techniques used in model validation, controls testing, and governance workflows.

Lead small, agile engineering teams focused on scalable and well-controlled model risk solutions.

Drive an AI-first approach to automate and enhance model risk management frameworks, workflows, and decision support.

Collaborate with stakeholders across risk, modeling, compliance, and technology teams to define priorities and deliver outcomes.

Ensure engineering solutions are resilient, auditable, and aligned to enterprise architecture, control, and data standards.

Support the evolution of model risk capabilities through strong technical leadership, disciplined execution, and stakeholder partnership.

Qualifications

Bachelor’s degree in Software Engineering, Computer Science, or a related field; advanced degree preferred.

Experience with model risk management, model validation processes, and quantitative techniques in enterprise environments.

Familiarity with agile practices and a track record of leading high-performing teams.

 

Ways of Working

Operate as a senior engineering leader within the Engineering Practice, contributing to engineering standards, talent development, and platform-wide execution discipline.

Work within the Risk & Compliance Hub to align delivery with hub priorities, regulatory expectations, and enterprise risk and control objectives.

Lead small, high-performing agile teams using iterative delivery practices, transparent prioritization, and measurable outcomes.

Partner closely with product, data, risk, compliance, and business stakeholders to shape roadmaps and deliver resilient solutions.

Promote an AI-first mindset by identifying opportunities to improve engineering productivity, automation, controls, and decision support.

Leadership Expectations

Create clarity on priorities, architecture direction, and execution outcomes for the team and stakeholders.

Build strong engineering culture through coaching, accountability, collaboration, and continuous improvement.

Balance innovation with sound engineering practices, operational resilience, and risk management.

Represent the domain effectively across hub, practice, and enterprise governance forums.

Drive delivery against strategic objectives while maintaining high standards for quality, performance, and control.