Director, Application Development Manager

BNY Mellon

$150K — $180K *
Enterprise Technology
11 - 15 years of experience
Job Overview by Ladders

Qualifications

  • Advanced degree in computer science or related field, or equivalent experience.
  • 12+ years of experience in systems analysis and program development, including supervisory roles.
  • Experience with operational risk management systems and workflows in enterprise settings.
  • Familiarity with agile methodologies and leading high-performing teams.
  • Strong communication skills and ability to influence and manage stakeholders.

Responsibilities

  • Design scalable architectures for operational risk controls and monitoring systems.
  • Standardize risk event taxonomies and controls management information.
  • Develop strategies for risk mitigation and resilient engineering capabilities.
  • Lead agile teams focused on platform delivery and operational stability.
  • Drive an AI-first approach to enhance automation and workflow effectiveness.
  • Collaborate with stakeholders to prioritize and deliver risk management capabilities.
  • Support balanced engineering decisions that promote innovation and risk management.

Benefits

  • Opportunity to work with cutting-edge AI technologies in operational risk engineering.
  • Engage in a collaborative and agile work environment.
  • Leadership role with a strong emphasis on professional development and talent cultivation.
  • Involvement in strategic engineering decisions affecting a major financial institution.
  • Ability to influence organizational standards and practices in engineering.
Full Job Description
Job Description

Role Summary: The Director, Head of Engineering - Operational Risk 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 Operational Risk domain, with a focus on scalable platforms, strong controls, agile execution, and an AI-first approach to engineering outcomes.

Key Responsibilities
  • Design scalable architectures for operational risk controls, event management, and monitoring systems.
  • Standardize taxonomies for operational risk events, controls, issues, and related management information.
  • Develop risk mitigation strategies, automation frameworks, and resilient engineering capabilities to strengthen the control environment.
  • Lead small, agile engineering teams focused on platform outcomes, delivery quality, and operational stability.
  • Drive an AI-first approach in operational risk tooling to improve automation, insight, and workflow effectiveness.
  • Collaborate with stakeholders in risk management, control functions, and business units to prioritize and deliver capabilities.
  • Support engineering decisions that balance innovation, risk management, and operational resilience.

Qualifications
  • Advanced degree in computer science or a related discipline, or equivalent work experience required12 + years of experience in systems analysis and program development with related supervisory, management and administrative experience required, experience in the securities or financial services industry is a plus
  • Experience with operational risk management systems, controls, or workflow tooling in an enterprise setting.
  • Familiarity with agile practices and leading small, high-performing teams.
  • Industry experience in operational risk is a plus.
  • Strong communication, influence, and stakeholder management skills.

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.


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