Program Manager - AI Engineering

Responsibilities

• Serve as a trusted partner and extension of AI Engineering leadership, helping drive strategic priorities across the organization.
• Operate with a high degree of autonomy, translating leadership direction into actionable plans and measurable outcomes.
• Represent leadership in meetings and stakeholder forums when needed.
• Develop executive communications, business reviews, and leadership presentations.
• Identify risks, dependencies, and opportunities, and proactively drive resolution.
• Lead a portfolio of AI, GenAI, and Agentic AI initiatives from ideation through production and optimization.
• Provide executive-level reporting on delivery status, risks, dependencies, and business outcomes.
• Establish and maintain governance practices supporting AI lifecycle management, risk controls, and regulatory requirements.
• Ensure programs align with enterprise standards and achieve target adoption, performance, and stability outcomes.
• Manage portfolio budgets, forecasts, funding allocations, and financial reporting.
• Oversee vendor relationships, including SOWs, contract governance, invoicing, and performance management.
• Develop workforce strategies including capacity planning, staffing optimization, resiliency, and critical skill development.
• Partner with leadership to build scalable operating models that support growing AI Engineering demand.
• Provide oversight of strategic initiatives, ensuring alignment between business objectives, engineering delivery, and investment priorities.
• Apply Agile and modern software delivery practices to improve execution and time-to-market.
• Drive alignment, decision-making, and accountability across complex cross-functional initiatives.

Qualifications

• 8+ years in program/portfolio management within technology organizations (banking preferred)
• Experience managing AI/ML, GenAI portfolios
• Technical Expertise & Understanding:
• AI/ML lifecycle (data, training, deployment, monitoring)
• GenAI and LLM-based solutions
• Agentic frameworks and orchestration patterns
• MLOps / AIOps practices
• Cloud platforms (AWS, Azure, GCP)
• Data engineering and big data ecosystems
• DevOps and CI/CD pipelines
• Financial & Operational Skills & Experience:
• Portfolio budgeting and forecasting
• Cost optimization strategies for cloud and AI workloads
• Vendor contract and SOW management
• Leadership & Execution:
• Demonstrated ability to lead complex, cross-functional portfolios
• Strong executive communication and reporting skills
• Proven ability to drive delivery stability and operational excellence at scale
• Regulatory & Risk Awareness:
• Understanding of model risk management, governance, and compliance within financial services
• Demonstrated Executive Partnership & Influence
• Supporting senior executives, business leaders, or technology leaders
• Representing leadership priorities across large organizations
• Influencing without direct authority
• Preparing executive-level presentations and communications
• Engaging confidently with senior stakeholders

Preferred Experience

• Chief of Staff, Business Operations, Strategic Initiatives, Portfolio Operations, or Executive Program Management experience
• Experience serving as a strategic advisor or operational extension to senior technology leaders
• Experience supporting board, executive committee, or senior leadership reviews