Director, Product Strategy & Roadmap

📍 Job Overview

Job Title: Director, Product Strategy & Roadmap

Company: Royal Bank of Canada

Location: Toronto, Ontario, Canada

Job Type: Full-Time

Category: Product Management / AI Strategy & Operations

Date Posted: 2026-09-16

Experience Level: 10+ Years

Remote Status: On-site

🚀 Role Summary

• Owns the end-to-end product strategy and roadmap for RBC's internal agentic AI platform, driving its evolution and adoption.

• Leverages deep expertise in agentic AI (LLMs, tool-use, MCP connectors, RAG, multi-agent orchestration) to define and deliver platform capabilities.

• Drives rigorous prioritization of features and initiatives based on user value, adoption evidence, and business impact.

• Partners closely with engineering teams on roadmap execution, ensuring delivery quality and alignment with product vision.

• Establishes and maintains robust product analytics and adoption dashboards to measure platform success and inform future development.

📝 Enhancement Note: This role is positioned at a Director level, indicating significant strategic responsibility and influence over the agentic AI platform's direction and success. The emphasis on "owning the roadmap" and "deciding what ships and when" highlights a strategic product leadership function rather than a purely execution-focused role. The requirement for fluency in agentic AI and partnership with engineering on technical implementation without direct coding responsibility suggests a strong need for a product leader who can bridge business needs with technical possibilities in a complex enterprise environment.

📈 Primary Responsibilities

• Strategic Roadmap Development: Define, maintain, and communicate a rolling 12-month product roadmap for the agentic AI platform, supported by clear, evidence-based prioritization rationale.

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

• End-to-End Product Experience Ownership: Oversee the complete user journey on the platform, from discovery and adoption to building and value realization, ensuring a coherent and intuitive experience for self-service builders, template users, and connector catalog interactions.

• Product Analytics & Measurement: Develop, implement, and maintain comprehensive adoption dashboards, usage telemetry, and value-realization metrics to guide product decisions and demonstrate platform ROI.

• Engineering Partnership & Delivery: Collaborate effectively with engineering teams on defining acceptance criteria, managing the backlog, and ensuring the quality of delivered features, acting as the guardian of the intended user outcome.

• 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 gate processes.

• Market & Competitive Analysis: Conduct ongoing analysis of the competitive landscape and market trends to inform strategic platform direction and identify new opportunities.

📝 Enhancement Note: The responsibilities clearly delineate a strategic product leadership role. The emphasis on "owning the end-to-end product experience" and "building and maintaining adoption dashboards" suggests a focus on user adoption and measurable business outcomes, which are critical for operations and GTM success. The explicit mention of "Responsible AI in practice" indicates a need for a product leader aware of and capable of integrating regulatory and ethical considerations into product development, a key aspect in financial services.

🎓 Skills & Qualifications

Education:

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

• Possession of a Product Management certification (e.g., AIPM, Pragmatic Institute, CSPO, SAFe) is considered a strong asset. Experience:

• Minimum of 8 years of progressive product management experience.

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

• Proven track record of owning and successfully delivering a product roadmap that has resulted in measurable adoption outcomes.

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

• Familiarity with AI governance frameworks such as NIST AI RMF, OSFI E-23, or equivalent is preferred. Required Skills:

• Product Strategy & Roadmap: Ability to define and articulate a clear product vision and strategy, translating it into actionable roadmaps.

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

• Product Analytics & Metrics: Proficiency in defining, tracking, and interpreting adoption metrics, usage telemetry, and value-realization data. Ability to build and maintain dashboards.

• Stakeholder Management: Excellent skills in capturing, assessing, and prioritizing requirements from diverse stakeholders across business lines and leadership.

• User Experience (UX) & Design Sensibility: Strong ability to shape the overall user experience, focusing on discoverability, adoption, and user success with the platform.

• Technical Fluency: Sufficient technical understanding to effectively partner with engineering on architecture and implementation decisions without direct coding responsibilities.

• Agile Delivery Methodologies: Expertise in backlog grooming, definition of acceptance criteria, and participation in agile development cycles.

• Market Analysis: Capability to conduct competitive and market analysis to inform product direction.

Preferred Skills:

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

• Experience with prompt engineering, model evaluation, or fine-tuning AI models in a production environment.

• Background working within 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 requirements emphasize a blend of strategic product thinking, deep technical understanding of cutting-edge AI, and strong analytical capabilities. The experience level and specific AI knowledge requirements position this as a senior leadership role within the product function, requiring a candidate who can not only define strategy but also deeply understand the underlying technology and its application in an enterprise setting. The "nice to have" skills like financial services awareness and experience with governance frameworks are critical for success within RBC.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Roadmap & Prioritization Examples: Showcase instances where you have developed and managed product roadmaps, detailing the prioritization process, the rationale behind decisions, and the resulting product outcomes.

• User Experience Design & Impact: Present case studies demonstrating your ability to influence and shape the end-to-end user experience of a product, including examples of how user feedback and adoption metrics informed design iterations.

• Product Analytics & Performance Dashboards: Include examples of dashboards or reports you have created to track key product adoption metrics, usage telemetry, and value realization. Explain how these insights drove product decisions.

• Agile Delivery Artifacts: Provide examples of backlog grooming, user stories, or acceptance criteria you have defined for features, illustrating your collaboration with engineering teams.

• AI/ML Product Case Studies: Detail specific AI/ML products you have managed, focusing on the challenges, the technologies used (e.g., LLMs, RAG), and the measurable impact achieved.

Process Documentation:

• Workflow Design & Optimization: Demonstrate experience in mapping out complex user workflows and identifying opportunities for optimization through AI-driven solutions.

• System Implementation & Automation: Showcase examples of how you have guided the implementation of new platform features or automated processes to enhance efficiency and user adoption.

• Measurement & Performance Analysis: Illustrate your approach to defining KPIs, collecting data, and analyzing performance to drive continuous improvement of the product and its underlying processes.

📝 Enhancement Note: For a role at this level, particularly in AI product management, a portfolio should emphasize strategic thinking, data-driven decision-making, and the ability to translate complex technical concepts into tangible product outcomes. The focus should be on demonstrating impact through metrics and clear articulation of the product development lifecycle, especially concerning AI technologies.

💵 Compensation & Benefits

Salary Range:

Based on industry benchmarks for Director-level Product Management roles in Toronto, with a specialization in AI/ML and enterprise platforms, the estimated annual base salary range is CAD $170,000 - $240,000. This range can vary based on the candidate's specific experience, qualifications, and performance during the interview process.

Benefits:

• Comprehensive Total Rewards Program: Includes competitive base salary, performance-based bonuses, and potential commissions/stock options where applicable.

• Flexible Benefits Package: Offers a range of health, dental, and vision coverage options to suit individual and family needs.

• Professional Development: Access to coaching, mentorship, and opportunities for leadership development to foster career growth.

• Retirement Savings Plans: Robust options for long-term financial planning.

• Employee Assistance Programs: Support services for personal and professional well-being.

• Paid Time Off: Generous vacation, sick leave, and holiday policies.

Working Hours:

• Standard full-time employment is 37.5 hours per week.

• While the role is on-site, RBC typically offers flexibility in work schedules to accommodate project needs and work-life balance, subject to team and operational requirements.

📝 Enhancement Note: The salary estimate is based on research of Director-level Product Management roles in Toronto's financial and technology sectors, considering the specialized nature of AI/ML and enterprise platform management. The benefits listed are standard for large financial institutions like RBC, with a focus on comprehensive support for employees. The provided working hours (37.5) are a standard baseline, but the "on-site" nature implies adherence to office hours, with potential for managed flexibility.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

RBC operates within the highly regulated and competitive global financial services industry. This context demands a strong emphasis on security, compliance, data integrity, and client trust. For an AI product role, this translates to a need for rigorous adherence to Responsible AI principles, robust data governance, and a deep understanding of the evolving regulatory landscape (e.g., OSFI E-23).

Company Size: Large Enterprise (Thousands of employees)

As one of Canada's largest banks, RBC offers the stability, resources, and scale of a major global institution. For operations and product professionals, this means opportunities to work on impactful, large-scale initiatives, collaborate with diverse teams, and navigate complex organizational structures. It also implies established processes and a structured approach to product development and implementation.

Founded: 1864

With a long history, RBC has a deep-rooted understanding of the financial markets and a strong reputation. This legacy influences its culture, emphasizing reliability, client focus, and long-term strategic planning. The company's ongoing investment in digital transformation and AI indicates a forward-looking approach that balances tradition with innovation.

Team Structure:

• AI Group Focus: This role sits within RBC's AI Group, a specialized function designed to accelerate AI adoption and scale AI opportunities across the bank. It's a newly formed, high-impact team working alongside experienced transformation leaders.

• Reporting & Collaboration: The Director will report into a leadership position within the AI Group and will collaborate extensively with engineering teams, business lines, AI governance, and other cross-functional partners. The structure is designed for agility and direct impact.

• Cross-Functional Collaboration: Success relies on seamless collaboration with engineering (for technical implementation), business lines (for user needs and adoption), AI governance (for compliance and safety), and potentially data science and research teams.

Methodology:

• Data-Driven Decision Making: Emphasis on using data, analytics, and user adoption metrics to inform roadmap prioritization and product strategy.

• Agile & Iterative Development: Application of agile methodologies for efficient product delivery, backlog management, and continuous improvement.

• Focus on User Value & Adoption: A core tenet is ensuring the platform provides tangible value to internal users and drives high adoption rates.

Company Website: jobs.rbc.com

📝 Enhancement Note: The context of RBC as a large, established financial institution is crucial. It implies a culture that balances innovation with risk management and compliance. The AI Group is positioned as a strategic accelerator, suggesting a dynamic environment within a larger, more structured organization. Understanding the needs of banking end-users and navigating the regulatory landscape will be key to success.

📈 Career & Growth Analysis

Operations Career Level: Director, Product Strategy & Roadmap

This role is a senior leadership position within product management, specifically focused on a critical emerging technology (agentic AI) within an enterprise context. It signifies a move beyond individual contribution or team lead to strategic ownership, influencing product direction, and driving significant business outcomes through technology. The focus is on strategic planning, market awareness, and influencing cross-functional teams.

Reporting Structure:

The Director will likely report to a Vice President or Senior Director within the AI Group. This position will require close collaboration with engineering leadership (e.g., Director of Engineering), product managers, and potentially heads of business units that will be primary users of the agentic AI platform. The structure emphasizes direct partnership and influence without direct line management of large engineering teams.

Operations Impact:

The Director's impact will be measured by the successful adoption and utilization of the internal agentic AI platform, leading to increased efficiency, improved decision-making, and enhanced productivity for various business lines within RBC. By owning the roadmap and user experience, this role directly contributes to RBC's broader AI transformation goals, amplifying the impact of its people and driving innovation at scale. Driving adoption of this platform can lead to significant cost savings, revenue enhancements, and improved client service indirectly.

Growth Opportunities:

• Strategic Leadership Advancement: Potential to move into higher-level product leadership roles (e.g., VP Product Management, Head of Product) within the AI Group or other technology divisions at RBC, leading larger product portfolios or broader strategic initiatives.

• Specialization in AI Product Management: Deepen expertise in agentic AI, generative AI, and enterprise AI platform development, becoming a recognized leader in this cutting-edge field within the financial industry.

• Cross-Functional Leadership: Opportunities to lead or mentor cross-functional teams involved in AI product development, driving strategic alignment and execution across different departments.

• Exposure to Senior Leadership: Direct engagement with senior executives across RBC, providing visibility and opportunities to influence strategic technology decisions at the highest levels.

📝 Enhancement Note: This role offers significant growth potential due to its strategic nature and focus on a high-priority technology area within a major financial institution. The path to broader product leadership or deep specialization in AI is clear, with ample opportunity for high-impact work and executive visibility.

🌐 Work Environment

Office Type: Hybrid/On-site with Collaborative Spaces

RBC Waterpark Place, 88 Queens Quay W, Toronto, is a modern office environment designed for collaboration and productivity. As an on-site role, the Director will work from this location, benefiting from the infrastructure and resources of a major corporate headquarters. The environment likely includes dedicated workspaces, meeting rooms, and common areas designed to foster interaction and teamwork.

Office Location(s):

RBC Waterpark Place, 88 Queens Quay W, Toronto, Ontario. This prime downtown Toronto location offers excellent accessibility via public transportation and is situated in a vibrant business district.

Workspace Context:

• Collaborative Environment: The office space is designed to support teamwork and cross-functional interaction, essential for a role that partners closely with engineering, business lines, and governance teams.

• Operations Tools & Technology: Access to RBC's standard suite of productivity, communication, and collaboration tools, along with specialized AI development and analytics platforms.

• Team Interaction: Frequent opportunities for direct interaction with the AI Group, engineering teams, and other stakeholders, facilitating rapid communication and problem-solving.

Work Schedule:

• Standard work hours are 37.5 hours per week.

• While the role is on-site, RBC emphasizes a culture that supports work-life balance, suggesting potential for some flexibility in daily scheduling, provided it aligns with team collaboration needs and project deadlines. The focus is on delivering results and maintaining strong stakeholder engagement.

📝 Enhancement Note: The on-site requirement in a major corporate office suggests a structured work environment with ample resources. The emphasis on collaboration indicates that the physical workspace is set up to facilitate team interaction, which is crucial for complex product development initiatives like an AI platform.

📄 Application & Portfolio Review Process

Interview Process:

The interview process for a Director-level role at RBC typically involves multiple stages designed to assess strategic thinking, leadership capabilities, technical depth, and cultural fit.

• Initial Screening: A recruiter or hiring manager will conduct an initial review of your application and resume, focusing on alignment with the core requirements.

• Hiring Manager Interview: A deep dive into your experience, especially regarding product management, AI/ML, roadmap ownership, and stakeholder management. Expect behavioral questions and scenario-based inquiries.

• Technical/Product Assessment: This may involve a case study or a presentation where you are asked to outline a product strategy, roadmap, or solve a specific product challenge related to agentic AI. This stage will assess your technical fluency and analytical skills.

• Panel Interview: You will likely meet with a panel of stakeholders, including engineering leaders, potential peers, and representatives from business units that will use the platform. This assesses cross-functional collaboration skills and how you handle diverse perspectives.

• Senior Leadership Interview: A final conversation with a senior executive (e.g., VP of AI Group) to evaluate strategic alignment, leadership potential, and overall fit with RBC's vision.

Portfolio Review Tips:

• Focus on Impact: For each case study, clearly articulate the problem, your role, the solution (product/feature), the metrics used to measure success, and the tangible outcomes (e.g., adoption rates, efficiency gains, cost savings).

• Demonstrate Strategic Thinking: Show how your product decisions aligned with broader business objectives and how you anticipated market trends or user needs.

• Showcase AI/ML Depth: For AI-related projects, detail the specific technologies used (LLMs, RAG, etc.), the challenges encountered in implementation or adoption, and how you addressed them.

• Prioritization Rationale: Be prepared to explain your prioritization framework and how you balanced competing demands from different stakeholders.

• User-Centricity: Highlight how user feedback, data analytics, and adoption metrics informed your roadmap and product iterations.

• Presentation Clarity: Ensure your portfolio is well-organized, visually appealing, and easy to understand. Practice presenting your key achievements concisely.

Challenge Preparation:

• Case Study Practice: Prepare for potential case studies by thinking through how you would approach defining a roadmap for an internal AI platform, prioritizing features, or addressing a specific adoption challenge.

• AI/ML Scenario Planning: Anticipate questions about the future of agentic AI, ethical considerations, or how to integrate AI into complex enterprise workflows.

• Stakeholder Management Scenarios: Prepare examples of how you have managed difficult stakeholder conversations, resolved conflicts, or gained buy-in for your product vision.

• Data & Analytics: Be ready to discuss how you define KPIs, use data to make decisions, and build reporting mechanisms for product performance.

📝 Enhancement Note: The interview process emphasizes a comprehensive evaluation of strategic, technical, and leadership skills. A strong portfolio that clearly demonstrates quantifiable impact and strategic thinking, particularly in AI product management, will be critical for success. The case study component is a key opportunity to showcase practical application of skills.

🛠 Tools & Technology Stack

Primary Tools:

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

• Agentic AI Frameworks & Libraries: Experience with frameworks facilitating LLM integration, tool use, and multi-agent orchestration. This could include libraries like LangChain, LlamaIndex, or proprietary internal tools.

• AI/ML Model Interaction: Proficiency in interacting with and managing Large Language Models (LLMs), understanding concepts like Retrieval Augmented Generation (RAG), and potentially fine-tuning or prompt engineering.

Analytics & Reporting:

• Business Intelligence Tools: Tableau, Power BI, Looker (or similar) for building and maintaining adoption dashboards and visualizing usage telemetry.

• Telemetry & Usage Tracking: Experience with analytics tools (e.g., Google Analytics, Mixpanel, Amplitude, or custom internal logging solutions) to capture user behavior and platform usage data.

• Data Warehousing/Lakes: Familiarity with querying data from enterprise data warehouses or data lakes (e.g., Snowflake, Databricks, SQL Server) to extract insights.

CRM & Automation:

• Internal Systems: While not a direct CRM role, understanding how the AI platform interacts with internal enterprise systems, potentially including CRM-like functionalities for user management or workflow automation.

• Workflow Automation Tools: Familiarity with tools or concepts related to automating business processes, which is a key outcome of agentic AI platforms.

• API Integration: Understanding of API design principles and experience integrating various services and platforms, crucial for the "connector catalog" aspect of the platform.

📝 Enhancement Note: The technology stack for this role is heavily focused on AI/ML development and product management tooling. A strong candidate will be proficient in using product management software, understanding AI/ML frameworks, and leveraging analytics tools to drive product decisions. The mention of "MCP connectors" and "self-service builder" implies a need for understanding platform architecture and integration capabilities.

👥 Team Culture & Values

Operations Values:

• Client First: A deep commitment to understanding and serving the needs of internal RBC users, ensuring the agentic AI platform delivers tangible value and enhances their productivity.

• Integrity: Upholding the highest ethical standards in AI development and deployment, ensuring safety, fairness, and transparency in all platform features and operations.

• Collaboration: Fostering a highly collaborative environment, working seamlessly with engineering, business lines, AI governance, and other stakeholders to achieve shared objectives.

• Respect: Valuing diverse perspectives and ensuring an inclusive environment where all team members feel empowered to contribute their best work.

• Excellence: Striving for continuous improvement, driving innovation, and delivering high-quality, impactful solutions that set new benchmarks for AI adoption within the organization.

Collaboration Style:

• Cross-Functional Integration: The role demands active integration with engineering teams for development, business lines for requirements and adoption, and governance teams for compliance, ensuring a holistic approach to product development.

• Process Review & Feedback: A culture of constructive feedback and continuous process improvement, encouraging open dialogue about what's working and what can be enhanced in the product lifecycle.

• Knowledge Sharing: Encouraging the sharing of insights, best practices, and learnings across teams, especially concerning AI capabilities, user adoption strategies, and operational efficiency gains.

📝 Enhancement Note: The values are aligned with RBC's stated corporate values, emphasizing client focus, integrity, and excellence. For this specific role, the emphasis on "Client First" translates to internal users, and "Integrity" directly relates to Responsible AI. The collaboration style highlights the need for strong interpersonal skills and the ability to work effectively across diverse functional groups.

⚡ Challenges & Growth Opportunities

Challenges:

• Navigating Enterprise Complexity: Balancing the need for rapid AI innovation with the inherent complexities, regulations, and established processes of a large financial institution like RBC.

• Driving Adoption of New Technology: Overcoming potential user inertia or resistance to adopting new AI tools and workflows, requiring strong change management and user enablement strategies.

• Keeping Pace with AI Evolution: The agentic AI landscape is rapidly evolving; continuously updating the platform's capabilities and strategy to remain at the forefront of innovation.

• Ensuring Responsible AI Implementation: Proactively embedding safety, fairness, and transparency into AI systems, which requires ongoing vigilance and collaboration with governance teams.

Learning & Development Opportunities:

• AI Skill Advancement: Deepen expertise in cutting-edge AI technologies, particularly agentic AI, LLMs, and their application in enterprise settings through hands-on experience and potential training.

• Industry Conferences & Certifications: Opportunities to attend leading AI and product management conferences, and potentially pursue advanced certifications relevant to AI governance or product leadership.

• Mentorship & Leadership Development: Benefit from mentorship from experienced transformation leaders within RBC's AI Group and participate in leadership development programs to hone strategic and management skills.

📝 Enhancement Note: The challenges presented are typical for roles introducing advanced technology in large, regulated environments. The growth opportunities are substantial, offering a path to deep specialization and broad leadership within a prominent financial institution.

💡 Interview Preparation

Strategy Questions:

• "Describe your process for developing and prioritizing a product roadmap for a complex enterprise platform, specifically an AI-driven one. How do you balance competing stakeholder demands?"

• "Walk us through a time you had to influence engineering to adopt a specific technical approach or architectural decision for a product. What was your strategy and the outcome?"

• "How would you approach defining and measuring the success of an internal agentic AI platform? What key metrics would you track, and how would you use that data to drive product decisions?" Company & Culture Questions:

• "What do you understand about RBC's approach to AI and digital transformation? How do you see this role contributing to that?"

• "Describe your experience working with cross-functional teams. How do you ensure alignment and effective collaboration, especially with technical and business stakeholders?"

• "How would you ensure that the agentic AI platform adheres to RBC's Responsible AI principles and governance frameworks? Provide an example of how you've integrated ethical considerations into a product." Portfolio Presentation Strategy:

• Structure: Organize your presentation logically: Problem -> Your Role/Solution -> Key Features/Technology -> Metrics/Results -> Learnings.

• Quantify Impact: Use specific numbers and data points to demonstrate the value and success of your past projects. For AI projects, highlight adoption rates, efficiency gains, or cost savings.

• Showcase Technical Fluency: Clearly explain the AI/ML technologies used (LLMs, RAG, etc.) and how they contributed to the solution, without getting overly technical unless prompted.

• Emphasize Strategic Vision: Connect your past work to the strategic goals of the role and RBC, demonstrating how you think about product evolution and market trends.

• Engage Your Audience: Be prepared to answer questions and facilitate a discussion about your work, showing enthusiasm and deep understanding.

📝 Enhancement Note: Interview preparation should focus on demonstrating a blend of strategic product leadership, deep AI/ML understanding, strong analytical skills, and proven ability to navigate complex organizations. The portfolio presentation is a critical opportunity to showcase these capabilities with concrete examples.

📌 Application Steps

To apply for this operations position:

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

• Portfolio Customization: Tailor your resume and any supplementary materials to highlight your experience with product strategy, roadmap development, agentic AI technologies (LLMs, RAG), product analytics, and stakeholder management. Quantify achievements wherever possible.

• Resume Optimization: Ensure your resume clearly articulates your 8+ years of product management experience, with specific emphasis on your 3+ years in AI/ML or enterprise platforms. Use keywords from the job description naturally.

• Interview Preparation: Thoroughly prepare for behavioral and situational questions. Practice articulating your thought process for roadmap prioritization, user experience design, and AI strategy. Be ready to present a concise overview of your most relevant portfolio pieces.

• Company Research: Deeply research RBC's AI strategy, its stated values (Client First, Integrity, Collaboration, Respect, Excellence), and its position in the financial services industry. Understand the importance of Responsible AI and governance frameworks within a bank.

⚠️ 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.