Work Location:

Hours:

Line of Business:

Pay Details:

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

Role mandate:

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.

Strategic leadership and thought leadership:

• 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.

Business value creation:

• 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.

AI products and capability development:

• 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.

Agentic transformation and future ways of working:

• 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.

Governance, risk, and responsible 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.

Decision authorities:

• 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.

Mandate scope: TD Securities front office with Global focus and enterprise applicability where capabilities are reusable across business lines.

The role has shared responsibilities and decision interfaces with:

• Front Office business leaders for opportunity prioritization, workflow design, commercial impact, user adoption, and value realization.

• Data Products for reusable business-ready data products, semantic business context, data quality expectations, lineage, provenance, metadata, and AI-ready information structures.

• Technology and Architecture partners for secure implementation, integration patterns, production readiness, platform alignment, resiliency, and sustainable support models.

• Risk, Compliance, Legal, Information Security, and enterprise AI Governance for responsible AI adoption, control design, policy alignment, approval pathways, and auditability.

• Finance and Business Management for business cases, benefits tracking, budget planning, operating leverage, and measurable value realization.

• Operations, Change Management, Human Resources, and Learning partners for adoption, training, workflow change, role impact, and capability building.

• Product and delivery partners for execution plans, stakeholder engagement, backlog prioritization, success metrics, and delivery discipline.

• Business value realized from AI-enabled products, capabilities, and workflow transformation initiatives.

• Delivery of approved roadmap milestones, business cases, benefits realization plans, and strategic transformation objectives.

• Productivity improvement, manual effort reduction, faster cycle times, improved insight generation, and reduced operational friction in supported front office workflows.

• Adoption, active usage, repeat usage, user satisfaction, and business sponsor satisfaction for AI-enabled tools and products.

• Number and maturity of reusable AI-enabled business capabilities, workflows, skills, patterns, and product components deployed or adopted.

• Team growth, talent development, stakeholder engagement, and cross-functional delivery effectiveness.

• Financial targets, portfolio budget, cost center budget, project budget, and value realization commitments to be confirmed.

• 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.

Education:

• Undergraduate degree required or equivalent practical experience.

• Masters or PhD preferred in, Computer Science, Engineering, Data Science, Artificial Intelligence, Mathematics, or a related discipline.

Experience and skills:

• 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.

• Capital markets or front office experience preferred, including knowledge of sales, trading, banking, client coverage, revenue generation, risk, controls, and operating model complexity.

• 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.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.

Interview Process 
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.

Accommodation