We are seeking a Lead Technology Project Manager AI to lead the delivery of strategic AI initiatives across Private Wealth Management. This role will play a critical part in enhancing advisor effectiveness, client engagement, and operational decision-making through responsible AI implementation.

The Lead Technology Project Manager AI will partner directly with the Director of Technology for PWM Engineering & Data to translate PWM’s AI strategy into executable delivery plans. This role will serve as a strategic liaison between engineering, data science, product, and business stakeholders, ensuring AI initiatives are aligned with advisor workflows and business priorities. The position offers high visibility across PWM leadership and vendor partners, with opportunities to influence strategic direction, drive measurable impact, and enhance delivery effectiveness using modern project management tools and practices.

Key Responsibilities

• Strategic Planning & Execution

  • Apply project management and systems development life cycle expertise to identify, plan, and execute complex AI initiatives that enhance PWM’s strategic goals. 
  • Collaborate with business partners to define project vision, scope, goals, and deliverables for AI platforms and solutions.
  • Develop comprehensive project plans, budgets, and stakeholder approval processes for both internal and vendor-led AI implementations through Agile program delivery.
  • Monitor status of project roadmap and individual initiatives, proactively resolving issues and escalating risks that may impact success.
  • Maintain current knowledge of AI and technology trends, best practices, and risks associated with emerging solutions. Share expertise with project teams and business unit leadership.
  • Oversee the use of technology project management tools (e.g., Jira, Azure DevOps) to enhance delivery effectiveness and ensure consistent execution across initiatives.
  • Proactively identify and resolve project issues; escalate risks and blockers to leadership as needed to maintain delivery momentum and alignment.
  • Stay current on AI and wealth management technology trends, evaluating their potential impact on PWM’s business strategy and platform evolution.

• Business Partnership

  • Develop strong relationships with PWM stakeholders and a deep understanding of advisor workflows, strategic goals, and business challenges.
  • Identify opportunities to leverage AI and automation to achieve business strategies and improve advisor productivity.
  • Collaborate with stakeholders to analyze project feasibility, cost/benefit, and strategic impact. Develop and maintain AI initiative roadmaps based on business priorities.

• AI Platform Evaluation & Implementation

  • Lead and manage both vendor-led and internally developed AI platforms, ensuring consistent execution standards, data integration, and stakeholder alignment across all initiatives.
  • Lead platform evaluation and implementation for AI vendor tools to drive Private Wealth Management initiatives.  Includes use case documentation, business requirements gathering, and integration planning.   
  • Manage internal AI platform initiatives in partnership with PWM’s AI Data Science team.
  • Coordinate with the firm’s Central Technologies/Infrastructure team and PWM’s Data Engineering team to ensure infrastructure readiness and data integration for AI platforms.

• Cross-Functional & Vendor Coordination

  • Drive agile sprint planning and execution across Data Engineering, Data Science, and external vendor teams.
  • Maintain clear communication with leadership and stakeholders throughout the AI project lifecycle.
  • Manage day-to-day operational aspects of AI projects, providing direction and support to internal teams and vendor partners.
  • Ensure projects meet timing, budget, and quality objectives. Update plans as needed to meet evolving business needs.
  • Ensure formal project closeout, including documentation of lessons learned, stakeholder reporting, and transition to ongoing support or enhancement phases.

• Change Management & Adoption

  • Support change management and AI solution adoption across the PWM business.
  • Ensure PWM’s AI solutions are designed with advisor workflows in mind, incorporating feedback loops and usability testing to drive adoption and impact.
  • Promote AI fluency by helping teams understand PWM’s AI capabilities, limitations, and use cases through documentation, demos, and training sessions.

Required Qualifications

• Bachelor’s Degree in Computer Science, Information Systems, or a related field;
• 7+ years of project/program management experience, including 3+ years delivering AI/ML, data science, or advanced analytics solutions.
• Proven ability to manage complex technical projects involving cloud-based data pipelines, ML models, and cross-functional teams.
• Expert project management skills across all phases: planning, budgeting, scheduling, execution, communication, documentation, and change management.
• Familiarity with the AI/Machine Learning lifecycle, including model development, validation, deployment, and monitoring.
• Robust experience managing AI vendor platform evaluation through end-to-end implementation, including data integrations.
• Strong vendor management experience and ability to influence outcomes without formal authority.
• Experience in financial services, ideally in wealth or management, asset management.
• Strong communication skills, with the ability to bridge technical detail and business impact.
• Commitment to quality and stakeholder satisfaction.
• Proficiency in collaboration tools such as Azure and M365 Copilot.

Preferred Qualifications 

• PMP, Agile, or Scrum certification.
• Master’s degree in a related field.
• Experience implementing wealth management AI initiatives such as generating client insights, automation of action items and workflows, reading statements and other documents, lead generation and prospecting, chatbots, research summarization, compliance automation.
• Familiarity with financial regulatory and compliance frameworks.
• Understanding of model risk management in regulated environments.
• Familiarity in platforms such as Databricks, Power BI, Python and SQL.

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