Director, Product Strategy & Roadmap

📍 Job Overview

Job Title: Director, Product Strategy & Roadmap

Company: Royal Bank of Canada (RBC)

Location: Toronto, Ontario, Canada

Job Type: Full-Time

Category: Product Management / AI Strategy

Date Posted: 2026-08-19

Experience Level: 8+ Years

Remote Status: On-site

🚀 Role Summary

• Owns the end-to-end product strategy and roadmap for RBC's internal agentic AI platform, focusing on prioritization, user value, and adoption metrics.

• Drives the product experience and analytics, ensuring the platform is usable and valuable at scale for internal users.

• Partners closely with engineering teams on roadmap execution without direct technical implementation oversight.

• Integrates responsible AI, safety, and governance standards into the platform's development lifecycle and release gates.

• Conducts market and competitive analysis to inform strategic direction and identify growth opportunities for the AI platform.

📝 Enhancement Note: While the title is "Director, Product Strategy & Roadmap," the core responsibilities and required experience strongly align with a senior Product Management role, specifically focused on an internal enterprise AI platform. The emphasis on "owning the roadmap," "prioritization," "user experience," and "partnership with engineering" are hallmarks of a Senior Product Manager or Group Product Manager role. The "Director" title might reflect the strategic impact and leadership required for this critical internal platform.

📈 Primary Responsibilities

• Roadmap Ownership & Prioritization: Maintain and clearly communicate a rolling 12-month product roadmap, providing evidence-based rationale for all prioritization decisions.

• Stakeholder Management & Intake: Systematically capture, assess, and prioritize feature requests and strategic initiatives from various business lines, end-users, and leadership teams against a defined value framework.

• Product Experience & Adoption: Define and own the complete user journey for the agentic AI platform, encompassing discovery, adoption, building capabilities, and value realization, including self-service builders, templates, and connector catalogs.

• Product Analytics & Measurement: Develop and manage adoption dashboards, usage telemetry, and value realization metrics to inform product decisions and demonstrate platform impact.

• Engineering Partnership: Collaborate with engineering teams on acceptance criteria, backlog refinement, and ensuring delivery quality to safeguard intended user outcomes.

• Responsible AI Integration: Embed safety, governance, and transparency standards, as defined by the AI Group's Safety and Responsible AI function, into the product roadmap and release approval processes.

• Market & Competitive Intelligence: Perform thorough analysis of the competitive landscape and market trends to inform the strategic direction and differentiation of the AI platform.

📝 Enhancement Note: The responsibilities highlight a deep focus on the "what" and "why" of product development rather than the "how" from a technical implementation perspective. This is characteristic of a senior product role responsible for strategic direction and business outcomes. The explicit mention of "partnering with engineering on acceptance criteria, backlog, and delivery quality" suggests a strong Product Owner role within an Agile framework.

🎓 Skills & Qualifications

Education:

• Bachelor's or Master's degree in Computer Science, Engineering, Business, Human-Computer Interaction (HCI), or a related discipline is preferred.

• Product management certifications such as AIPM, Pragmatic Institute, CSPO, or SAFe are considered a strong asset. Experience:

• Minimum of 8 years of progressive product management experience.

• At least 3 years of direct experience with AI/ML products or complex enterprise platforms.

• Proven track record of owning and successfully delivering a product roadmap with measurable adoption outcomes.

• Experience building developer platforms, APIs, or self-service builder tools is highly desirable.

• Familiarity with AI governance frameworks like NIST AI RMF, OSFI E-23, or equivalent is a plus. Required Skills:

• Product Strategy & Roadmap Development: Ability to define and articulate a clear product vision, strategy, and a data-driven roadmap.

• Agentic AI Expertise: Deep working understanding of agentic AI concepts including LLMs, tool-use, MCP connectors, RAG, and multi-agent orchestration.

• Product Analytics & Metrics: Strong analytical skills with the ability to define, track, and interpret adoption metrics, build dashboards, and analyze telemetry data.

• Stakeholder Management: Proven ability to effectively engage with, gather requirements from, and influence diverse stakeholder groups across business lines and leadership.

• Technical Fluency: Sufficient technical understanding to partner effectively with engineers on architecture and technical decisions without writing code.

• Agile Delivery: Expertise in Agile methodologies, including backlog grooming, acceptance criteria definition, and sprint planning.

• User Experience (UX) Sensibility: A strong product-experience and design sensibility to shape user journeys, adoption, and success with a product.

Preferred Skills:

• Financial services industry awareness, with an understanding of banking end-users (advisors, analysts, operations staff) and their workflow needs.

• Experience with prompt engineering, model evaluation, or fine-tuning in production environments.

• Background in a fintech, regtech, or a major bank's digital transformation team.

• Familiarity with AI governance frameworks (NIST AI RMF, OSFI E-23, or equivalent).

📝 Enhancement Note: The required experience level (8+ years, with 3+ in AI/ML) positions this as a senior leadership role within product management, suitable for someone who can drive strategic initiatives and mentor others. The emphasis on specific AI technologies like LLMs, RAG, and agentic AI indicates a highly specialized and forward-looking role.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Roadmap Visualization: Examples of roadmaps that clearly articulate strategic priorities, timelines, and key initiatives, showcasing prioritization rationale.

• Metrics & Analytics Dashboards: Demonstrations of how data and analytics were used to drive product decisions, track adoption, and measure value realization. Include examples of key metrics and dashboard designs.

• User Journey Mapping: Case studies or examples illustrating how user experience was considered and shaped for a complex platform or enterprise tool.

• Process Optimization Case Studies: Projects that highlight improvements to internal processes or workflows, achieved through the implementation or enhancement of technology solutions.

Process Documentation:

• Requirement Gathering & Prioritization Frameworks: Examples of how user needs and business requirements were captured, analyzed, and prioritized for product development.

• Agile Workflow Management: Evidence of experience managing product backlogs, defining acceptance criteria, and collaborating with engineering teams in an Agile environment.

• Performance Measurement & Reporting: Documentation of how product performance was measured, tracked, and reported to stakeholders, focusing on adoption and business impact.

📝 Enhancement Note: For a role at this level, a strong portfolio demonstrating strategic thinking, data-driven decision-making, and impactful product delivery is crucial. The emphasis should be on strategic impact, not just feature lists. Candidates should be prepared to discuss their process for translating business needs into actionable product roadmaps and measuring success.

💵 Compensation & Benefits

Salary Range:

• Given the "Director" title, extensive experience (8+ years), specialized AI/ML product management expertise, and location in Toronto (a major financial hub), a competitive salary range is expected. For a Director-level Product role in Toronto in the financial services sector, the estimated annual base salary would likely fall between CAD $160,000 and CAD $220,000. This range can vary based on the candidate's specific experience, qualifications, and performance during the interview process. Benefits:

• Comprehensive Total Rewards Program including bonuses, flexible benefits, competitive compensation, commissions, and stock options where applicable.

• Opportunities for professional development and coaching from experienced leaders.

• Exposure to senior leadership across RBC, offering significant visibility and networking potential.

• Contribution to driving AI transformation at a leading financial institution. Working Hours:

• Standard full-time hours (approximately 37.5 hours per week), with potential for flexibility depending on project needs and team agreements. The role is primarily on-site, implying a structured work schedule within the office environment.

📝 Enhancement Note: The salary estimate is based on industry benchmarks for Director-level Product Management roles in Toronto's financial services sector, considering the specialized AI/ML focus. The provided benefits list is directly from the job description and highlights a comprehensive package typical of large financial institutions. The 37.5 working hours per week indicate a standard professional schedule.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

Company Size: Large Enterprise (RBC is one of Canada's largest banks, with tens of thousands of employees globally). This size implies a structured environment with established processes, significant resources, and broad impact potential. For operations professionals, this can mean opportunities for specialization, career progression, and working on large-scale initiatives.

Founded: 1864 (Long history as a stable and established financial institution).

Team Structure:

• The role sits within RBC's AI Group, described as an "AI accelerator" focused on scaling AI projects and delivering client outcomes.

• This is a newly formed, high-impact function, suggesting a dynamic and potentially fast-paced environment within a larger, established organization.

• The team likely comprises experienced transformation leaders and AI specialists.

• This Director will partner with engineering, likely meaning close collaboration with technical leads, architects, and development teams. Methodology:

• Data-Driven Decision Making: Emphasis on evidence-based prioritization, user value, adoption evidence, and product analytics.

• Agile Delivery: Partnership with engineering implies an Agile framework, with responsibilities for backlog grooming and acceptance criteria.

• Responsible AI & Governance: A strong focus on embedding safety, governance, and transparency standards, reflecting industry best practices and regulatory considerations.

• User-Centric Design: Ownership of the end-to-end product experience, focusing on how users discover, adopt, and derive value.

Company Website: https://jobs.rbc.com/ca/en

📝 Enhancement Note: RBC's culture emphasizes strong values like Client First, Integrity, Collaboration, Respect, and Excellence. The AI Group's mission to accelerate AI adoption and scale impact suggests an innovative and forward-thinking environment within a traditional financial institution. The "newly formed" nature of the group implies opportunities to shape processes and culture.

📈 Career & Growth Analysis

Operations Career Level: Director, Product Strategy & Roadmap. This is a senior leadership position, responsible for the strategic direction and execution of a critical internal AI platform. It implies significant autonomy and responsibility for driving business outcomes through product innovation.

Reporting Structure:

• The role reports into the AI Group, likely to a VP or Senior Director overseeing AI product initiatives.

• Direct collaboration with engineering leadership and key stakeholders across business lines is expected. Operations Impact:

• This role has a direct impact on improving internal operational efficiency, empowering employees (advisors, analysts, operations staff) with advanced AI tools, and driving AI transformation across RBC.

• Success in this role can lead to significant improvements in productivity, service delivery, and innovation within the bank. Growth Opportunities:

• Leadership Expansion: Potential to lead larger product teams, manage multiple AI platforms, or move into broader AI strategy or innovation roles within RBC.

• Skill Specialization: Deepening expertise in agentic AI, responsible AI, and enterprise platform product management.

• Cross-Functional Leadership: Developing broader business acumen and leadership skills through extensive stakeholder engagement across various banking functions.

• Industry Influence: Contributing to the advancement of AI product management practices within the financial services sector.

📝 Enhancement Note: The "Director" title and the strategic nature of owning an end-to-end roadmap for a critical platform suggest a significant growth trajectory. Candidates are expected to not only manage the product but also influence its strategic direction and the broader AI adoption within RBC.

🌐 Work Environment

Office Type: On-site at RBC Waterpark Place, Toronto. This indicates a traditional office setting within a major corporate headquarters.

Office Location(s): RBC WATERPARK PLACE, 88 QUEENS QUAY W: TORONTO. This is a prime downtown Toronto location, offering excellent accessibility and proximity to amenities.

Workspace Context:

• Collaborative Environment: The emphasis on "collaboration" as a core RBC value and the nature of the role (stakeholder intake, engineering partnership) suggests a highly collaborative office environment.

• Tools & Technology: Access to advanced internal systems, collaboration tools, and likely state-of-the-art IT infrastructure necessary for AI development and product management.

• Team Interaction: Opportunities for regular interaction with a diverse group of professionals within the AI Group, engineering teams, and business units.

Work Schedule:

• Approximately 37.5 hours per week, with the expectation of dedication to achieving strategic objectives. While primarily on-site, there might be some flexibility for specific needs, but the core expectation is presence in the office.

📝 Enhancement Note: The on-site requirement in a major financial hub like Toronto suggests a professional and structured work environment. Candidates should anticipate working in a corporate setting with a focus on collaboration and adherence to established corporate practices, balanced with the innovative drive of the AI Group.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Resume and application review, likely focusing on alignment with required experience and AI/ML product management expertise.

• Hiring Manager Interview: Discussion focused on product strategy, roadmap ownership, AI/ML knowledge, and leadership capabilities.

• Panel Interviews: Likely to include interviews with engineering leads, other product managers, and key business stakeholders to assess technical fluency, collaboration style, and strategic alignment.

• Portfolio Presentation: Candidates may be asked to present a case study or walk through their portfolio, demonstrating their approach to product strategy, roadmap development, prioritization, and impact measurement.

• Final Round: Potential discussion with senior leadership within the AI Group to assess strategic fit and long-term potential.

Portfolio Review Tips:

• Strategic Focus: Showcase how you've translated business objectives into tangible product strategies and roadmaps. Highlight your role in defining the "what" and "why."

• Data-Driven Rationale: Be prepared to detail how you used data, user feedback, and market analysis to justify roadmap decisions and prioritize initiatives.

• Agentic AI Fluency: Include examples where you've applied or managed products involving LLMs, RAG, or other agentic AI components. Explain the challenges and successes.

• Impact & Outcomes: Quantify the impact of your work using metrics related to user adoption, efficiency gains, or business value.

• Collaboration & Partnership: Illustrate how you've successfully partnered with engineering, design, and business teams to deliver complex products.

Challenge Preparation:

• Be ready to discuss a hypothetical scenario for prioritizing features on the agentic AI platform roadmap, considering limited resources and diverse stakeholder needs.

• Prepare to articulate your approach to defining and measuring the success of an internal AI platform.

• Think about how you would integrate "Responsible AI" principles into a product roadmap and delivery process.

📝 Enhancement Note: The interview process will likely be rigorous, assessing both strategic product thinking and practical execution skills. A strong portfolio that clearly articulates past successes, particularly in AI/ML product management, will be critical. Candidates should be prepared to demonstrate their understanding of agentic AI and its application in an enterprise context.

🛠 Tools & Technology Stack

Primary Tools:

• Product Management Platforms: Jira, Confluence, Aha!, Productboard, or similar for roadmap planning, backlog management, and documentation.

• AI/ML Platforms: While not directly building, familiarity with platforms that support LLMs, RAG, agentic orchestration (e.g., LangChain, Microsoft Azure AI, AWS SageMaker, Google AI Platform) is crucial for partnership with engineering.

• Data Analysis & Visualization: Tools like Tableau, Power BI, Looker, or custom internal dashboards for tracking adoption, usage telemetry, and value realization.

Analytics & Reporting:

• Telemetry & Monitoring: Tools for collecting and analyzing user interaction data and system performance.

• Business Intelligence (BI) Tools: For creating dashboards and reports to communicate key performance indicators (KPIs) to stakeholders.

CRM & Automation:

• While this is an internal platform, understanding how it might integrate with or complement existing CRM systems (e.g., Salesforce, Dynamics 365) or workflow automation tools could be beneficial for context.

📝 Enhancement Note: The role requires deep familiarity with product management tools and a strong understanding of the technologies and platforms that power agentic AI. While the candidate won't be coding, they must be technically fluent enough to engage in meaningful discussions with engineers about architecture, capabilities, and limitations.

👥 Team Culture & Values

Operations Values:

• Excellence: Driving high standards in product strategy, roadmap execution, and user experience for the AI platform.

• Collaboration: Working seamlessly with engineering, business lines, and AI governance teams to achieve shared objectives.

• Integrity: Upholding ethical standards in AI development and ensuring responsible AI practices are embedded.

• Client First (Internal): Focusing on the needs of internal users (advisors, analysts, operations staff) to ensure the platform delivers maximum value and usability.

• Respect: Fostering an inclusive environment where diverse perspectives are valued in product development and decision-making.

Collaboration Style:

• Cross-Functional Integration: Proactive engagement with engineering, AI safety, legal, compliance, and business units to align on strategy and execution.

• Data-Informed Discussions: Using metrics and analytics to drive conversations and decisions, ensuring objectivity and evidence-based approaches.

• Transparent Communication: Maintaining open and clear communication channels regarding roadmap progress, challenges, and strategic shifts.

• Partnership with Engineering: Acting as a strategic partner to engineering, providing clear direction and vision while respecting technical expertise.

📝 Enhancement Note: The role demands a blend of strategic vision and collaborative execution. Candidates should be able to articulate how they embody RBC's core values, particularly "Excellence" and "Collaboration," in the context of developing and deploying advanced AI technologies.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Innovation and Governance: Navigating the rapid evolution of AI with strict financial industry regulations and responsible AI requirements.

• Prioritization Complexity: Managing competing demands from various internal stakeholders for a platform with broad applicability.

• Adoption at Scale: Driving widespread adoption and effective utilization of a new AI platform across a large, diverse workforce.

• Technical Partnership: Effectively collaborating with engineering on complex AI technologies without direct technical implementation control.

Learning & Development Opportunities:

• AI Advancement: Staying at the forefront of agentic AI, LLMs, and related technologies through continuous learning and industry engagement.

• Financial Services AI: Deepening understanding of AI applications within the banking sector and navigating regulatory landscapes.

• Leadership Development: Opportunities to refine leadership, strategic planning, and stakeholder management skills in a high-impact role.

• Mentorship: Access to experienced leaders within RBC's AI Group and the broader organization.

📝 Enhancement Note: The challenges are inherent to pioneering AI within a regulated financial institution. The growth opportunities are significant, offering a chance to become a leader in AI product strategy within a major bank.

💡 Interview Preparation

Strategy Questions:

• "How would you prioritize feature requests for an internal agentic AI platform with limited engineering resources, given competing demands from different business units?" (Focus on your framework, data inputs, and stakeholder management).

• "Describe your process for defining and measuring the success of an AI product, specifically an internal platform aimed at improving employee productivity." (Highlight metrics, dashboards, and value realization).

• "How do you ensure 'Responsible AI' principles are integrated into a product roadmap and development lifecycle from inception to delivery?" (Discuss governance, safety checks, and transparency). Company & Culture Questions:

• "What are your thoughts on RBC's stated values, and how would you apply them in your role as Director, Product Strategy & Roadmap for the AI Group?" (Connect values to your work).

• "How would you foster collaboration between the Product team, Engineering, and the AI Safety/Governance teams?" (Discuss communication strategies and partnership approaches).

• "Given RBC's position as a large financial institution, how would you approach driving adoption of a new AI platform among diverse employee groups?" (Focus on change management, training, and user support). Portfolio Presentation Strategy:

• Structure: Organize your portfolio around key projects, clearly outlining the problem, your strategic approach, the roadmap you developed, key decisions made (and why), challenges overcome, and quantifiable outcomes.

• AI Focus: Highlight any experience with AI/ML products, especially LLMs or enterprise platforms. Explain your understanding of the technology's capabilities and limitations.

• Metrics & Impact: Dedicate time to showcasing how you measured success and demonstrated ROI or business value. Use clear, impactful numbers.

• Conciseness: Be prepared to present concisely and answer detailed questions. Aim for 15-20 minutes for the presentation, leaving ample time for Q&A.

📝 Enhancement Note: Interview preparation should focus on demonstrating strategic product thinking, deep understanding of AI/ML (particularly agentic AI), strong analytical skills, and effective stakeholder management. Be ready to discuss how you translate complex technical capabilities into business value and operational efficiency.

📌 Application Steps

To apply for this operations position:

• Submit your application through the official RBC careers portal using the provided link.

• Portfolio Customization: Tailor your resume and cover letter to highlight your experience with product strategy, roadmap development, agentic AI, product analytics, and stakeholder management. Prepare specific examples of your work that align with the responsibilities outlined.

• Resume Optimization: Ensure your resume clearly showcases 8+ years of product management experience, with a minimum of 3 years in AI/ML or enterprise platforms. Quantify achievements wherever possible using metrics related to adoption, efficiency, or business impact.

• Interview Preparation: Practice articulating your approach to product strategy, prioritization, and AI implementation. Prepare to discuss specific case studies from your portfolio, focusing on your role and the outcomes achieved.

• Company Research: Thoroughly research RBC, its AI Group's mission, and its core values. Understand the financial services industry context and the unique challenges and opportunities of deploying AI within a regulated environment.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.