Position OverviewThe Associate Director, Transformation Management will lead complex, cross-functional strategic and operational initiatives across Apollo's global platform. This role sits at the intersection of business strategy, digital enablement, and AI-driven operating model redesign. This individual will champion AI-first process redesign, institutionalize measurable value creation, and ensure transformation initiatives are executed with rigor, accountability, and alignment to Apollo's risk and governance standards.
Primary Responsibilities- Lead large-scale, cross-functional transformation initiatives from strategy through execution, accountable for scope, timelines, budget, risk management, and measurable outcomes
- Redesign core operating workflows using AI-first principles, embedding automation, decision intelligence, and human-in-the-loop controls into target-state processes
- Translate complex business challenges into AI-enabled operating models that improve scalability, risk management, operating leverage, and decision velocity
- Conduct detailed current-state assessments, including process mapping, data flow analysis, and control evaluation, and develop future-state designs with clear performance metrics
- Build value realization frameworks that quantify and track efficiency gains, quality improvements, risk reduction, capacity creation, and financial impact resulting from AI-driven redesign
- Institutionalize repeatable methodologies for AI-enabled business process reengineering, including governance standards, control frameworks, model risk considerations, and performance measurement
- Develop executive-level materials and financial analyses to support prioritization, investment approval, and steering committee decision-making
- Serve as a senior stakeholder manager, driving alignment across business leaders, executive sponsors, and control functions while fostering a culture of continuous improvement and responsible innovation
- Ensure redesigned workflows align with regulatory requirements, operational risk standards, and firmwide governance expectations
Qualifications & Experience- 6-8+ years of experience in corporate strategy, management consulting, digital transformation, or operational improvement, with increasing ownership of complex initiatives
- Demonstrated experience leading enterprise-scale transformation efforts involving technology, data, and operating model redesign
- Strong fluency in artificial intelligence and automation concepts, including machine learning applications, intelligent workflow automation, model governance considerations, and AI risk management frameworks
- Superior analytical and financial modeling skills, with the ability to connect operational improvements to measurable economic value
- Executive-level communication skills, including the ability to distill complex, multi-dimensional issues into clear recommendations for senior leadership
- Proven ability to manage diverse stakeholders with competing priorities while maintaining momentum and accountability
- Bachelor's degree from an accredited institution or equivalent experience; advanced degree (e.g., MBA or relevant technical master's degree) preferred
- Experience within financial services, asset management, insurance, or other highly regulated environments
- Direct experience deploying AI-enabled solutions into production environments, including change management and adoption strategies
- Experience building value tracking dashboards or performance measurement frameworks tied to transformation initiatives
- Demonstrated ability to institutionalize best practices and build scalable transformation playbooks across an organization
Pay Range$175,000 - 225,000
The contents of the qualifications and experience section of this job description are a guideline only. If an applicant can otherwise demonstrate their suitability for the role they will be considered.
The base salary range for this position is listed above. This position is also eligible for a discretionary annual bonus based on personal, team, and Firm performance. Compensation ranges are based on several factors including job function, level, and geographic location. Final offer amounts are determined by multiple factors including candidate experience and expertise, and may vary from the amounts listed here.
