Director, Product Strategy & Roadmap

📍 Job Overview

Job Title: Director, Product Strategy & Roadmap

Company: RBC

Location: Toronto, Ontario, Canada

Job Type: Full time

Category: Product Management / AI Product Strategy

Date Posted: August 18, 2026

Experience Level: 10+ Years

Remote Status: On-site

🚀 Role Summary

• Lead end-to-end product roadmap development and execution for RBC's internal agentic AI platform, driving strategic prioritization based on user value and adoption evidence.

• Define and own the product experience, ensuring usability and value realization at scale through rigorous analytics, user adoption metrics, and telemetry.

• Partner closely with engineering teams to translate product vision into actionable development plans, ensuring delivery quality without direct technical implementation oversight.

• Embed critical safety, governance, and transparency standards from the AI Group's Responsible AI function into the product roadmap and release processes.

• Conduct thorough market and competitive analysis to continuously inform and refine the platform's strategic direction and future capabilities.

📝 Enhancement Note: This role is positioned within a Technology and Operations domain, focusing on a specialized area of AI product development, specifically agentic AI. The emphasis is on strategic product leadership, roadmap ownership, and cross-functional collaboration, rather than deep technical implementation or traditional Revenue/Sales Operations. The "Director" title and the nature of AI platform ownership suggest a senior-level position with significant influence over product direction and resource allocation.

📈 Primary Responsibilities

• Strategic Roadmap Ownership: Develop, maintain, and communicate a rolling 12-month product roadmap for the agentic AI platform, clearly articulating the rationale behind prioritization decisions and ensuring alignment with business objectives.

• Intake and Prioritization Management: Establish and manage a robust process for capturing, assessing, and prioritizing feature requests from various business lines, users, and leadership, ensuring all decisions are grounded in a consistent value framework.

• End-to-End User Experience Ownership: Define and own the complete user journey for the agentic AI platform, encompassing discovery, adoption, self-service building capabilities, template utilization, and connector catalog integration to create a cohesive and intuitive user experience.

• Product Analytics and Measurement: Design, build, and maintain comprehensive adoption dashboards, usage telemetry, and value realization metrics to provide actionable insights that drive product decisions and demonstrate platform impact.

• Engineering Delivery Partnership: Collaborate closely with engineering teams on backlog grooming, defining acceptance criteria, and ensuring delivery quality, acting as the voice of the user and product to protect the intended user outcome.

• Responsible AI Integration: Proactively embed safety, governance, and transparency standards, as defined by the AI Group's Safety and Responsible AI function, into the product roadmap, release gates, and ongoing product development lifecycle.

• Market and Competitive Intelligence: Conduct ongoing market analysis, competitive landscape assessments, and industry trend monitoring to inform platform strategy, identify emerging opportunities, and maintain a competitive edge.

📝 Enhancement Note: The responsibilities highlight a strong focus on product strategy, user experience, and data-driven decision-making within the domain of AI. This is distinct from traditional operations roles which might focus on CRM, sales processes, or marketing automation. The emphasis on "agentic AI," "LLMs," and "multi-agent orchestration" indicates a highly specialized technical product domain.

🎓 Skills & Qualifications

Education:

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

• Possess or be pursuing a product management certification (e.g., AIPM, Pragmatic Institute, CSPO, SAFe) is a plus. Experience:

• Minimum of 8+ years of progressive product management experience.

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

• Proven track record of owning and delivering a product roadmap that has demonstrated measurable adoption outcomes. Required Skills:

• Product Strategy & Roadmap Development: Expertise in defining product vision, strategy, and translating it into actionable, evidence-based roadmaps.

• Agentic AI Fluency: Deep working understanding of agentic AI concepts including Large Language Models (LLMs), tool-use, MCP connectors, Retrieval-Augmented Generation (RAG), and multi-agent orchestration.

• Data Analytics & Measurement: Strong analytical capabilities with demonstrated experience in defining and tracking adoption metrics, building dashboards, and interpreting telemetry data.

• User Experience (UX) Design Sensibility: A keen product-experience and design sense, with the ability to shape how users discover, adopt, and succeed with a product beyond just feature sets.

• Agile Delivery Expertise: Proficiency in agile methodologies, including backlog grooming, sprint planning, and defining clear acceptance criteria for engineering teams.

• Technical Fluency: Sufficient technical understanding to effectively partner with engineers on architecture decisions and understand technical implications without direct coding.

• Stakeholder Management: Proven ability to capture, assess, and prioritize feature requests from diverse stakeholders, including business lines and leadership.

Preferred Skills:

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

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

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

• Background within a fintech, regtech, or a digital innovation team at a major bank.

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

📝 Enhancement Note: The required skills heavily emphasize AI/ML product management, strategic roadmap planning, and analytical rigor. This is a specialized role that requires a blend of technical understanding, business acumen, and user-centric design principles within a complex financial services environment. The "Nice to have" section provides clear pathways for candidates to differentiate themselves.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Product Strategy & Roadmap Case Studies: Showcase examples of developed product strategies and roadmaps for AI or enterprise platforms, detailing the rationale, prioritization framework, and outcomes achieved.

• User Experience Design & Adoption: Present evidence of owning and improving end-to-end product experiences, including user journey mapping, adoption metrics, and how user feedback was incorporated.

• Data Analytics & Measurement Frameworks: Demonstrate experience in defining key performance indicators (KPIs) for AI products, building adoption dashboards, and utilizing telemetry data to inform product decisions. Include examples of value realization measurement.

• Cross-Functional Collaboration & Delivery: Provide examples of successful partnerships with engineering teams, illustrating contributions to backlog grooming, acceptance criteria definition, and ensuring delivery quality in an agile environment.

Process Documentation:

• Roadmap Prioritization Process: Document the methodology used for stakeholder intake, value assessment, and evidence-based prioritization of features for AI products.

• User Adoption & Engagement Strategy: Outline processes for driving user discovery, adoption, and ongoing engagement with AI platforms, including self-service tools and templates.

• Product Analytics & Reporting Process: Detail the approach to defining, collecting, and analyzing product usage telemetry and adoption metrics, and how this data feeds into product iteration.

• Responsible AI Integration Process: Describe how safety, governance, and transparency standards are embedded into the product development lifecycle, from roadmap planning to release gates.

📝 Enhancement Note: For a role at this level, a portfolio is crucial. It should not only showcase past successes but also demonstrate a structured, data-driven approach to product management, particularly within the specialized domain of AI. The focus should be on strategic thinking, user impact, and quantifiable results.

💵 Compensation & Benefits

Salary Range:

• Based on industry benchmarks for a Director-level Product Strategy role in Toronto, Canada, with 10+ years of experience in AI/ML product management within financial services, the estimated salary range is CAD $160,000 - $220,000 annually. This range accounts for the seniority, specialized skills in agentic AI, and the responsibilities associated with owning a critical internal platform at a major financial institution like RBC. Benefits:

• Comprehensive Total Rewards Program.

• Annual Bonuses.

• Flexible Benefits package.

• Competitive Compensation structure.

• Potential for Commissions and Stock Options (where applicable).

• Opportunities for professional development and coaching.

• Access to employee assistance programs and wellness initiatives. Working Hours:

• Standard full-time employment, typically 37.5 hours per week.

• The role operates within a standard business schedule, but may require flexibility to accommodate project deadlines, global team interactions, and urgent product-related issues.

📝 Enhancement Note: The salary range is an estimate based on industry data for senior product management roles in Toronto, Canada, with a specialization in AI. The benefits listed are directly from the provided text, highlighting RBC's commitment to employee well-being and professional growth.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking and Financial Technology)

Company Size: Large Enterprise (RBC is one of Canada's largest and most respected financial institutions, employing tens of thousands globally).

Founded: 1864 (Royal Bank of Canada).

Team Structure:

• AI Group: This role sits within RBC's AI Group, described as the "AI accelerator for RBC." This suggests a central, high-impact function focused on scaling AI initiatives and advancing research.

• Reporting Structure: The role reports to a leadership position within the AI Group, likely a VP or Senior Director of Product, with close collaboration expected across engineering, AI research, business lines, and potentially a dedicated Responsible AI function.

• Cross-functional Collaboration: Extensive collaboration is expected with engineering teams, AI researchers, business line stakeholders, product managers from various departments, and potentially legal, compliance, and risk teams due to the AI governance requirements.

Methodology:

• Data-Driven Decision Making: A strong emphasis on using evidence, user value, adoption metrics, and telemetry to guide roadmap prioritization and product development.

• Agile Development: Partnership with engineering implies adherence to agile methodologies for iterative development, backlog management, and delivery.

• Responsible AI Practices: A core methodology is the integration of safety, governance, and transparency standards into all stages of the AI product lifecycle.

• User-Centric Design: Focus on how users discover, adopt, build with, and derive value from the platform, indicating a user-centric approach to product experience.

Company Website: https://www.rbcroyalbank.com/

📝 Enhancement Note: RBC's culture is characterized by its "shared values" (Client First, Integrity, Collaboration, Respect, Excellence) and a commitment to diversity and inclusion. The AI Group is positioned as an innovative, fast-paced unit driving digital transformation within a large, established financial institution. This context is crucial for understanding the operational environment and expectations.

📈 Career & Growth Analysis

Operations Career Level: Director, Product Strategy & Roadmap

This role represents a senior leadership position within the product management function, specifically focused on a cutting-edge technology domain (agentic AI). It signifies a move beyond individual contributor or junior management roles, involving strategic decision-making, significant cross-functional influence, and ownership of a critical platform's direction and success. The scope of responsibility for an "end-to-end roadmap" and "platform experience" at a large institution like RBC indicates substantial impact and visibility.

Reporting Structure:

The role reports into the AI Group, likely under a VP or Senior Director of Product. This places it within a strategic technology innovation hub, with direct exposure to senior leadership across RBC. The position requires close partnership with engineering leadership, product teams in various business units, and specialized functions like Responsible AI.

Operations Impact:

The Director will drive AI transformation at RBC by scaling the internal agentic AI platform. This impact is measured through:

• Efficiency Gains: Enabling business lines and users to leverage AI for increased productivity and effectiveness.

• Innovation Acceleration: Providing the tools and infrastructure for employees to develop and deploy AI solutions more rapidly.

• Value Realization: Directly contributing to measurable business outcomes through improved workflows and enhanced capabilities powered by AI.

• Responsible AI Leadership: Ensuring that AI is developed and deployed ethically and compliantly, mitigating risks and building trust.

Growth Opportunities:

• Leadership Advancement: Potential to move into higher leadership roles within the AI Group, such as VP of Product Management, Head of AI Product, or similar strategic positions overseeing broader AI portfolios.

• Specialization Deepening: Opportunity to become a recognized expert in agentic AI, LLMs, and AI platform development within the financial services industry.

• Cross-Functional Mobility: Potential to transition into broader product leadership roles across different technology domains or business units within RBC, leveraging expertise in AI and strategic product management.

• Mentorship & Team Building: Opportunity to mentor junior product managers, shape the product management discipline within the AI Group, and contribute to building a high-performing product team.

📝 Enhancement Note: The career path for this role is clearly within senior product leadership, with a strong emphasis on AI and technology strategy. Growth is likely to involve expanding scope, managing larger teams, or taking on more strategic advisory roles within the organization's digital transformation efforts.

🌐 Work Environment

Office Type: The role is designated as "On-site" with a primary location at "RBC WATERPARK PLACE, 88 QUEENS QUAY W: TORONTO". This suggests a modern, professional office environment typical of major corporate headquarters.

Office Location(s):

• Primary Location: RBC Waterpark Place, 88 Queens Quay West, Toronto, Ontario, Canada. This is a prominent downtown Toronto location, likely offering excellent amenities and accessibility. Workspace Context:

• Collaborative Environment: RBC emphasizes "collaboration" and "winning together as One RBC." The office space is likely designed to foster team interaction, with shared workspaces, meeting rooms, and common areas.

• Technology & Tools: As a technology-focused role within a major bank, expect access to cutting-edge technology, robust IT infrastructure, and a suite of collaboration and productivity tools necessary for AI product development and management.

• Operations Team Interaction: The role is situated within the AI Group, suggesting a dynamic environment filled with AI specialists, engineers, researchers, and product professionals. This provides ample opportunities for knowledge sharing, problem-solving, and cross-pollination of ideas.

Work Schedule:

• The standard work schedule is full-time, typically 37.5 hours per week.

• While the role is on-site, RBC likely offers a degree of flexibility within the standard working day to accommodate individual needs and team collaboration schedules, common in modern corporate environments.

📝 Enhancement Note: The on-site requirement at a prime Toronto location indicates a structured corporate environment. The emphasis on collaboration and technology suggests a modern, well-equipped workspace designed for innovation and team synergy.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and application to assess alignment with the core requirements, particularly experience in AI product management and strategic roadmap development.

• Hiring Manager/Team Interview: A detailed discussion focusing on your experience with agentic AI technologies, product strategy formulation, roadmap ownership, and stakeholder management. Expect behavioral questions related to collaboration and problem-solving.

• Case Study/Presentation: Candidates may be asked to present a case study based on a past product initiative, focusing on strategic decision-making, roadmap execution, user adoption, and measurable outcomes. This is where portfolio elements will be critical.

• Technical/Engineering Partnership Discussion: An interview with engineering leaders to assess your technical fluency, ability to partner effectively on architecture, and understanding of AI development lifecycles.

• Cross-Functional/Leadership Interview: A final interview with senior leaders within the AI Group or relevant business units to evaluate strategic thinking, cultural fit, and overall leadership potential.

Portfolio Review Tips:

• Strategic Impact: Clearly articulate the business problem your product solved, the strategic objectives of the roadmap, and how your decisions drove value.

• Agentic AI Focus: For relevant projects, detail your understanding and application of LLMs, RAG, multi-agent orchestration, and related technologies.

• Data-Driven Rationale: Showcase how you used data (adoption metrics, telemetry, user feedback) to inform your roadmap and product decisions. Quantify results wherever possible.

• User Experience Ownership: Highlight your contribution to the end-to-end user experience, not just feature delivery. Show how you ensured the product was usable and valuable.

• Collaboration Evidence: Include examples of effective partnerships with engineering, design, and business stakeholders.

• Responsible AI Integration: If applicable, demonstrate how you incorporated safety, governance, or ethical AI considerations into your product development process.

Challenge Preparation:

• Roadmap Scenario: Be prepared to discuss how you would approach prioritizing features for an agentic AI platform given competing demands from different business units.

• Metrics Definition: Practice defining key metrics for AI platform adoption and value realization.

• Technical Partnership: Think about how you would communicate complex product requirements to engineers and how you would collaborate on technical trade-offs.

• Responsible AI Scenarios: Consider how you would address ethical considerations or potential risks associated with AI deployment.

📝 Enhancement Note: The interview process is designed to assess strategic thinking, deep technical understanding of AI, strong analytical skills, and leadership capabilities. A well-curated portfolio demonstrating these skills with tangible results will be essential for success.

🛠 Tools & Technology Stack

Primary Tools:

• CRM & Product Management Platforms: Tools like Jira, Confluence, Aha!, Productboard for roadmap management, backlog grooming, and feature request tracking.

• Agentic AI Frameworks: Proficiency with frameworks and libraries related to LLMs, RAG, and multi-agent orchestration (specific tools may vary, but understanding the concepts is key).

• Data Analytics & Visualization: Tools such as Tableau, Power BI, Looker, or custom Python/SQL-based solutions for building adoption dashboards and analyzing telemetry.

• Collaboration Tools: Microsoft Teams, Slack, Zoom for communication and virtual collaboration.

Analytics & Reporting:

• Telemetry & Usage Tracking: Experience with platforms for collecting and analyzing user interaction data (e.g., Amplitude, Mixpanel, Google Analytics, or internal logging systems).

• Data Warehousing & SQL: Ability to query and manipulate data from data warehouses (e.g., Snowflake, Redshift, BigQuery) using SQL.

• Business Intelligence (BI) Tools: Familiarity with BI platforms for creating and sharing reports and dashboards.

CRM & Automation:

• Internal Platform Development: While not a traditional CRM, the role involves managing an internal platform, requiring an understanding of how users interact with and build within it.

• Workflow Automation Concepts: Understanding of how AI agents can automate complex workflows.

• Integration Tools: Awareness of how AI platforms integrate with other enterprise systems.

📝 Enhancement Note: The technology stack emphasizes tools for product management, data analytics, and AI development. While specific internal RBC tools will be used, the candidate should demonstrate proficiency with industry-standard platforms and a strong understanding of AI-specific technologies.

👥 Team Culture & Values

Operations Values:

• Excellence: A drive for high-quality product delivery, data integrity, and impactful AI solutions that push the boundaries of what's possible.

• Collaboration: A commitment to working effectively with diverse teams across engineering, research, business lines, and governance functions to achieve shared goals.

• Integrity: Upholding the highest standards of ethical AI development, data privacy, and responsible innovation, aligning with RBC's core values.

• Client First (Internal): Focusing on the needs of internal users and business lines to ensure the agentic AI platform provides maximum value and enhances their work.

• Respect: Valuing diverse perspectives and fostering an inclusive environment where all team members feel heard and respected.

Collaboration Style:

• Partnership-Oriented: Works closely with engineering to define technical requirements and ensure quality, acting as a key partner rather than a client.

• Data-Informed Dialogue: Engages stakeholders with data and evidence to support roadmap decisions and product direction.

• Cross-Functional Alignment: Proactively seeks alignment with business units, AI researchers, and governance teams to ensure the platform meets diverse needs and complies with regulations.

• Transparent Communication: Maintains open and transparent communication regarding roadmap progress, challenges, and priorities.

📝 Enhancement Note: The team culture is shaped by RBC's overarching values, with a specific focus on innovation, ethical AI, and collaborative delivery within the AI Group. Expect a dynamic environment that blends corporate structure with the agility required for cutting-edge technology development.

⚡ Challenges & Growth Opportunities

Challenges:

• Pace of AI Evolution: Keeping pace with the rapid advancements in agentic AI, LLMs, and related technologies to ensure the platform remains cutting-edge and competitive.

• Balancing Innovation with Governance: Navigating the complex landscape of AI safety, governance, and regulatory compliance while still driving innovation and delivering features rapidly.

• Cross-Functional Alignment: Ensuring consistent prioritization and adoption across diverse business lines with potentially competing needs and varying levels of AI readiness.

• Measuring True Value: Quantifying the adoption and tangible business value of an internal AI platform can be complex, requiring sophisticated measurement strategies.

• Technical Complexity: Managing a platform built on rapidly evolving AI technologies requires continuous learning and adaptation.

Learning & Development Opportunities:

• AI Specialization: Deepen expertise in agentic AI, LLMs, RAG, multi-agent orchestration, and related AI technologies through hands-on experience and potentially specialized training.

• Financial Services AI: Gain unparalleled insight into the application of AI within a major financial institution, understanding the unique challenges and opportunities in this sector.

• Leadership Development: Opportunities to hone leadership skills in strategic product management, team building, and influencing senior stakeholders.

• Industry Engagement: Potential to attend industry conferences, engage with AI research communities, and contribute to the broader AI discourse.

• Cross-Organizational Exposure: Work with various departments, gaining a holistic understanding of RBC's operations and strategic priorities.

📝 Enhancement Note: The challenges are inherent to working with advanced AI in a regulated industry. The growth opportunities are significant, offering a chance to become a leader in a critical, high-impact technology area within a major global organization.

💡 Interview Preparation

Strategy Questions:

• "Describe your process for developing and maintaining a product roadmap for an AI platform. How do you balance competing stakeholder demands with technical feasibility and strategic goals?"

• "How would you define success for an internal agentic AI platform? What key metrics would you track, and how would you demonstrate its value to senior leadership?"

• "Walk me through a time you had to make a difficult prioritization decision for a product roadmap. What was the situation, what was your process, and what was the outcome?" Company & Culture Questions:

• "Based on your understanding of RBC and the AI Group, how would you ensure the agentic AI platform aligns with the company's values of 'Client First,' 'Integrity,' and 'Excellence'?"

• "How do you approach building relationships and driving alignment with engineering teams and business stakeholders who may have different priorities or levels of technical understanding?"

• "Describe your experience embedding responsible AI principles (safety, governance, transparency) into a product roadmap and development process." Portfolio Presentation Strategy:

• Structure Your Narrative: For each case study, clearly outline the problem, your strategic approach, the specific AI technologies used (agentic AI, LLMs, RAG), your role in roadmap development and prioritization, the user experience considerations, and the quantifiable business impact.

• Highlight Data & Metrics: Showcase how you used data (adoption rates, usage telemetry, ROI metrics) to support your decisions and demonstrate success.

• Emphasize Partnership: Detail your collaboration with engineering, design, and business stakeholders, illustrating your ability to work effectively in a cross-functional environment.

• Address Responsible AI: If applicable, explain how ethical considerations, safety, or governance were integrated into your product's lifecycle.

• Conciseness and Clarity: Be prepared to present your key findings and insights concisely, focusing on the most impactful aspects of your work.

📝 Enhancement Note: Preparation should focus on demonstrating strategic product thinking, deep expertise in AI technologies, a data-driven approach, and strong collaborative leadership. The portfolio should serve as tangible evidence of these capabilities.

📌 Application Steps

To apply for this Director, Product Strategy & Roadmap position:

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

• Tailor your Resume: Ensure your resume highlights your experience in product management, specifically with AI/ML products, agentic AI technologies (LLMs, RAG), strategic roadmap development, data analytics, and stakeholder management. Quantify achievements and responsibilities wherever possible.

• Prepare Your Portfolio: Curate a selection of 2-3 key projects that best demonstrate your strategic thinking, roadmap ownership, user experience focus, data-driven decision-making, and experience with AI technologies. Be ready to present these in detail.

• Research RBC and the AI Group: Understand RBC's mission, values, and its strategic focus on AI. Familiarize yourself with the AI Group's objectives as described in the job posting.

• Practice Interview Responses: Prepare answers to common product management, AI strategy, and behavioral questions, focusing on your experience and how it aligns with the role's requirements. Practice articulating your portfolio case studies clearly and concisely.

⚠️ 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.