AVP, AI & Innovation

TD•New York, NY

1d•$200,000 - $280,000•Onsite

About The Position

Lead the front office AI products, business transformation, and innovation capability for TD Securities. The role is accountable for identifying, designing, validating, and scaling AI-enabled tools, workflows, and business capabilities that create measurable value, improve decision quality, increase productivity, and strengthen client coverage and execution across front office functions. This role provides business ownership, product strategy, adoption leadership, and value realization for AI-enabled front office capabilities. It partners with Technology, Data, Risk, Compliance, Legal, Information Security, and enterprise AI teams.

Requirements

Undergraduate degree required or equivalent practical experience.
Typically 12 or more years of progressive experience in financial services, capital markets, business transformation, analytics, modeling or AI.
Deep understanding of AI, generative AI, agentic AI, workflow automation, analytics, decision support, and emerging business technology trends.
Strong technical acumen sufficient to challenge designs, understand architecture trade-offs, assess AI feasibility, evaluate technical risk, and partner credibly with data, engineering, and technology teams.
Strong business product leadership experience, including opportunity identification, product strategy, business case development, value realization, adoption, and lifecycle management.
Demonstrated ability to lead senior business stakeholders through complex transformation, influence executive decision making, and translate strategic vision into practical execution.
Experience building or scaling reusable capabilities, operating models, governance frameworks, or transformation programs across multiple stakeholder groups.
Excellent executive communication, storytelling, stakeholder management, negotiation, and change leadership skills.
Strong people leadership capability with experience developing multidisciplinary teams and building new organizational capabilities.

Nice To Haves

Masters or PhD preferred in, Computer Science, Engineering, Data Science, Artificial Intelligence, Mathematics, or a related discipline.
Capital markets or front office experience preferred, including knowledge of sales, trading, banking, client coverage, revenue generation, risk, controls, and operating model complexity.

Responsibilities

Develop and execute the vision, strategy, roadmap, and adoption model for AI-enabled business capabilities across TD Securities front office domains.
Act as a senior thought leader on AI, generative AI, agentic workflows, human-agent operating models, decision intelligence, and future-of-work opportunities for the business.
Translate emerging AI capabilities into practical business strategies, use cases, products, operating models, and value creation opportunities.
Educate and influence senior executives and business leaders on AI opportunities, risks, adoption priorities, and investment choices.
Shape business priorities for AI transformation by connecting market trends, client needs, front office workflows, and organizational strategy.
Identify and prioritize AI opportunities, build business cases, value hypotheses, adoption plans, and value realization frameworks for AI-enabled initiatives.
Ensure initiatives are anchored in business outcomes, not technology novelty, including clear measures of impact, adoption, usability, control readiness, and strategic value.
Partner with front office leaders to redesign workflows where AI can augment human judgment, automate routine work, accelerate insight creation, or improve execution quality.
Drive commercialization and operational adoption of AI capabilities so that solutions become embedded in business processes rather than remaining pilots.
Lead development of reusable AI products, decision-support capabilities, workflow tools, and agent-enabled business services.
Establish product management disciplines for AI-enabled capabilities, including product vision, roadmaps, lifecycle management, prioritization, adoption, and value tracking.
Design capabilities that reuse trusted data products, semantic business context, approved workflows, and governed AI patterns wherever possible.
Create scalable business capabilities that can be reused across desks, business lines, regions, or functions rather than building isolated one-off solutions.
Partner with Data Products on data readiness, semantic definitions, productized data assets, quality expectations, lineage, and AI-ready information structures.
Lead business adoption of agent-enabled workflows and human-agent collaboration models that improve how work is performed across the front office.
Partner with engineering, data, and technology teams to shape human-agent delivery models while ensuring business ownership, value realization, and adoption.
Identify opportunities to scale validated capabilities into repeatable patterns, reusable assets, and marketplace-style catalogs for broader adoption.
Partner with Risk, Compliance, Legal, Information Security, Technology, and enterprise AI governance teams to ensure responsible, controlled, auditable, and explainable adoption.
Ensure human accountability remains clear for material business decisions while enabling safe automation and augmentation where appropriate.
Define operating guardrails, escalation paths, adoption controls, measurement routines, and governance artifacts for AI products and agentic workflows.
Prioritize the AI products and business transformation portfolio in partnership with front office sponsors and enabling partners.
Evaluate roadmaps, value realization plans, adoption priorities, and capability incubation plans.
Recommend workflow redesign, operating model changes, and investment priorities required to scale AI-enabled business capabilities.
Develop standards for AI product ownership, adoption, lifecycle management, business readiness, and front office value measurement.
Escalate material risk, control, data, compliance, or technology dependencies to appropriate accountable partners for decision or remediation.
Improves the quality, speed, and consistency of client coverage by equipping front office teams with AI-enabled insights, workflow tools, and decision-support capabilities.
Accelerates responsiveness to client needs by reducing manual effort, improving access to relevant business context, and streamlining information discovery.
Supports revenue generation and relationship management by helping business teams identify opportunities, prepare more effectively, and act on insights faster.
Improves employee experience and execution quality by simplifying fragmented workflows and embedding intelligence into day-to-day business processes.
Strengthens control, transparency, and consistency by ensuring AI-enabled business capabilities are governed, explainable, reusable, and aligned to responsible adoption expectations.