AI Engineer - Full Stack Agentic UX

📍 Job Overview

Job Title: AI Engineer - Full Stack Agentic UX

Company: Royal Bank of Canada

Location: Toronto, Ontario, Canada; Vancouver, British Columbia, Canada

Job Type: Full-time

Category: Technology & Engineering / AI Engineering

Date Posted: August 12, 2026

Experience Level: 5-10 Years (Estimated)

Remote Status: On-site

🚀 Role Summary

• Design and develop sophisticated human-agent interaction patterns for an enterprise AI platform, focusing on progressive autonomy and explainable AI to build practitioner trust.

• Build full-stack AI-driven capabilities that automate complex workflows, integrating with corporate systems and calibrating human-AI coordination for optimal task completion.

• Implement robust trust and transparency mechanisms, including confidence signals and audit trails, to provide users with clear visibility into AI operations.

• Shape the user experience for diverse personas, creating accessible and trustworthy onboarding, progressive disclosure, and feedback mechanisms for AI-powered tools.

📝 Enhancement Note: The role requires a strong blend of full-stack engineering, UX design principles, and a deep understanding of human-AI interaction within a regulated financial services context. The focus on "Agentic UX" implies a need to design experiences that enable AI agents to perform complex, multi-step tasks autonomously or semi-autonomously, while ensuring user control, trust, and transparency. This is a key differentiator for advanced AI roles.

📈 Primary Responsibilities

• Design and implement advanced human-agent interaction patterns, incorporating principles of progressive autonomy, intent previews, and explainable AI to ensure practitioners maintain control and trust.

• Develop and deploy full-stack AI-driven capabilities that leverage the enterprise AI platform's orchestration layer to automate complex business workflows, carefully balancing human oversight with AI execution.

• Engineer trust and transparency features, such as confidence signals, action audit trails, and clear escalation pathways, to provide users with insight into AI decision-making processes and actions.

• Build and maintain enterprise integrations connecting AI capabilities to critical corporate platforms, including project management, collaboration suites, source control systems, and communication tools.

• Define and refine user onboarding flows, progressive disclosure strategies, and feedback loops to make the AI platform intuitive and reliable for a wide range of user profiles and technical proficiencies.

• Establish and manage the capability development lifecycle, from initial authoring and rigorous testing to quality validation and seamless deployment, to ensure a scalable catalog of AI-powered workflows.

• Create flexible extensibility models that empower teams and community contributors to author, share, and deploy custom AI capabilities on top of the core platform.

• Collaborate closely with platform engineering teams to ensure all developed capabilities and integrations are aligned with the platform's core orchestration, governance, and distribution infrastructure.

📝 Enhancement Note: The responsibilities highlight a need for proactive system design and lifecycle management. The emphasis on "authoring and testing through quality validation and deployment" suggests a structured MLOps or AI development process is expected, requiring candidates to demonstrate experience in the end-to-end development of AI features.

🎓 Skills & Qualifications

Education: While not explicitly stated, a Bachelor's or Master's degree in Computer Science, Engineering, Human-Computer Interaction, or a related field is typically expected for this level of role.

Experience: Estimated 5-10 years of progressive experience in full-stack software engineering, with a significant focus on AI-driven applications and user experience design.

Required Skills:

• Proficient full-stack engineering expertise in Python and/or TypeScript, with a proven track record of building production-grade, user-facing tools and complex integrations.

• Strong UX design sensibility, with the ability to translate intricate agentic workflows into intuitive and accessible interaction patterns for diverse user personas.

• Solid understanding of human-agent interaction principles, including trust calibration, progressive autonomy, transparency, and maintaining user control in AI-driven experiences.

• Familiarity with AI/LLM-powered tools, prompt engineering techniques, and agentic AI development patterns.

• Demonstrated experience building integrations with enterprise APIs (REST, GraphQL, SOAP) and connecting to corporate systems.

• Proven ability to collaborate effectively with cross-functional teams, including solution architects, business analysts, and project managers. Preferred Skills:

• Prior experience designing and developing AI-powered products like copilots, agents, or intelligent workflow tools where user trust and transparency are paramount.

• Background in design systems, component architecture, or the creation of AI-consumable design patterns.

• Experience within financial services technology or other highly regulated industries, understanding governance and compliance requirements.

• Familiarity with developer experience tooling, internal developer platforms (IDPs), or plugin ecosystem development.

📝 Enhancement Note: The "Must Have" skills indicate a strong preference for engineers who bridge the gap between backend AI/ML logic and frontend user experience. The "Nice to Have" skills suggest that candidates with domain-specific experience in financial services or familiarity with developer tools will have a competitive edge, pointing towards the strategic importance of this role within RBC's technology operations.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Showcase examples of full-stack applications developed, highlighting the integration of AI/ML components and user-facing interfaces.

• Present case studies demonstrating experience in designing and implementing complex workflows, particularly those involving automation or AI-assisted decision-making.

• Include projects that illustrate the application of UX design principles to technical products, with a focus on user control, transparency, and trust.

• Provide evidence of building integrations with various enterprise APIs and systems, detailing the technical challenges and solutions implemented. Process Documentation:

• Document the design and development process for at least one complex AI-driven feature or workflow, detailing the stages from ideation to deployment.

• Illustrate how you have implemented mechanisms for trust and transparency in AI systems, such as audit trails, confidence scoring, or explainability features.

• Demonstrate experience with the capability development lifecycle, including authoring, testing, quality validation, and deployment of AI components.

• Show examples of how you have contributed to or designed extensibility models for platforms or tools.

📝 Enhancement Note: For this role, a portfolio is crucial. It should not only demonstrate technical proficiency but also the ability to translate complex AI concepts into user-friendly experiences. Emphasis should be placed on projects that showcase the ability to build trust and manage risk in AI systems, especially given the financial services context.

💵 Compensation & Benefits

Salary Range: Based on industry benchmarks for AI Engineers with 5-10 years of experience in major Canadian financial hubs like Toronto and Vancouver, the estimated annual salary range is CAD $120,000 - $180,000. This range can vary based on the candidate's specific experience, skills, and performance during the interview process.

Benefits:

• A comprehensive Total Rewards Program including bonuses and flexible benefits.

• Competitive compensation structure, potentially including commissions and stock options where applicable.

• Access to leaders who provide coaching and management opportunities for professional development.

• World-class training programs tailored for the financial services industry.

• Support for flexible work/life balance options.

• Opportunities to engage in challenging and impactful work.

Working Hours: The standard working hours are 37.5 hours per week. While the role is on-site, the company emphasizes flexible work/life balance options, suggesting potential flexibility within the standard work week.

📝 Enhancement Note: The estimated salary range is based on data from reputable compensation sources for AI and Software Engineering roles in Canada, adjusted for the specific experience level and the financial services sector. The stated benefits align with typical large enterprise offerings, with a particular emphasis on professional development and work-life balance, which are attractive to senior technical talent.

🎯 Team & Company Context

🏢 Company Culture

Industry: Financial Services (Banking)

Company Size: Large Enterprise (RBC is one of the largest banks globally). This implies a structured environment with established processes, significant resources, and a broad impact.

Founded: 1864. RBC has a long-standing history, suggesting stability, deep industry expertise, and a commitment to long-term growth and client relationships.

Team Structure:

• The AI Engineer will be part of a team focused on building the user experience layer for an enterprise AI platform. This team likely operates within a larger Technology & Operations division, collaborating closely with platform engineering and AI governance groups.

• Reporting structure is likely to be to an Engineering Manager or Lead within an AI product development group, with direct interaction with product managers, UX designers, and other AI engineers.

• Cross-functional collaboration is a core tenet, involving partnerships with solution architects, business analysts, project managers, and potentially business line stakeholders who will utilize the AI capabilities. Methodology:

• Data Analysis and Insights: Employed to understand user behavior, AI performance metrics, and identify areas for improvement in agentic workflows and UX.

• Workflow Planning and Optimization: Central to designing and refining the multi-step agent workflows that form the core of the platform's value proposition.

• Automation and Efficiency Practices: Key to the role, focusing on leveraging AI to automate complex tasks and improve operational efficiency across the organization.

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

📝 Enhancement Note: RBC's emphasis on "Client First, Integrity, Collaboration, Respect and Excellence" and "winning together as One RBC" indicates a culture that values teamwork, ethical conduct, and customer-centricity. For an AI Engineer, this means ensuring that AI solutions are not only technically sound but also aligned with these core values, especially concerning governance, transparency, and ethical AI deployment in a regulated environment.

📈 Career & Growth Analysis

Operations Career Level: This role is positioned as an experienced AI Engineer, likely mid-to-senior level (5-10 years). It demands not just coding proficiency but also strategic thinking in designing user experiences for advanced AI systems. The scope includes developing core capabilities and influencing the platform's adoption through user-centric design.

Reporting Structure: The AI Engineer will likely report to an Engineering Manager or Director within RBC's technology division, specifically within a team dedicated to AI platform development or AI-powered solutions. Close collaboration with product management and UX design teams is expected.

Operations Impact: This role has a direct impact on operational efficiency and productivity by building AI capabilities that automate complex workflows. By creating trustworthy and effective agentic UX, the engineer will drive the adoption of AI across the organization, leading to significant gains in how teams work and deliver value to clients. The success of the enterprise AI platform hinges on the user experience designed by this role.

Growth Opportunities:

• AI Specialization: Deepen expertise in agentic AI, LLM orchestration, prompt engineering, and human-AI interaction design.

• Technical Leadership: Progress into a Senior AI Engineer, Staff Engineer, or Technical Lead role, guiding architectural decisions and mentoring junior engineers.

• Product Management/Strategy: Transition into roles focused on AI product strategy, defining roadmaps, and understanding market needs for AI solutions.

• Cross-functional Mobility: Opportunities to move into related areas like AI governance, MLOps, or specialized enterprise integration roles within RBC.

• Leadership Development: Access to RBC's leadership development programs for aspiring managers and directors within technology.

📝 Enhancement Note: The role offers a clear path for growth within a large financial institution, moving from individual contribution to technical leadership or strategic product roles. The emphasis on AI in a regulated industry provides unique learning opportunities in governance, compliance, and building trust in AI systems, which are highly valuable career assets.

🌐 Work Environment

Office Type: The role is designated as "On-site," implying a traditional office environment within RBC's corporate locations. This fosters in-person collaboration, team cohesion, and direct mentorship.

Office Location(s):

• RBC Centre, 155 Wellington St W, Toronto, Ontario, Canada

• Vancouver, British Columbia, Canada (specific address not provided, but likely a major RBC office). Workspace Context:

• Collaborative Environment: The on-site nature encourages spontaneous discussions, whiteboard sessions, and direct feedback loops essential for complex software and UX design.

• Operations Tools & Technology: Access to RBC's robust internal IT infrastructure, development tools, and potentially specialized AI/ML platforms and cloud environments.

• Team Interaction: Frequent opportunities for interaction with AI engineers, platform architects, UX designers, product managers, and business analysts, fostering knowledge sharing and problem-solving.

Work Schedule: Standard full-time employment with 37.5 working hours per week. While on-site, RBC offers "Flexible work/life balance options," which may include some flexibility in daily start/end times or occasional remote work arrangements, subject to team and business needs.

📝 Enhancement Note: The on-site requirement, common in large financial institutions for roles involving sensitive data and complex system development, is balanced by RBC's stated commitment to work-life balance. Candidates should expect a structured, professional office setting conducive to deep technical work and collaborative problem-solving.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter will review applications and conduct an initial screening call to assess basic qualifications and cultural fit.

• Technical Assessment: Candidates will likely undergo one or more technical interviews focusing on full-stack development skills (Python/TypeScript), API integration, and potentially coding challenges.

• AI/UX Deep Dive: Interviews will delve into understanding of human-agent interaction, prompt engineering, UX design for AI, and experience with agentic workflows. This may involve discussing portfolio projects in detail.

• System Design/Architecture: A session focused on designing solutions for complex AI-driven features, including considerations for scalability, trust, and integration within RBC's ecosystem.

• Behavioral & Cultural Fit: Interviews with hiring managers and team members to assess problem-solving approach, collaboration style, and alignment with RBC's values (Client First, Integrity, Collaboration, Respect, Excellence).

• Final Round: Potentially a discussion with senior leadership or a final executive interview.

Portfolio Review Tips:

• Curate Select Projects: Choose 2-3 projects that best showcase your full-stack capabilities, AI/agentic UX experience, and API integration skills.

• Structure Case Studies: For each project, clearly outline the problem, your role, the technical solutions implemented (including AI/UX aspects), the challenges faced, and the measurable outcomes or impact. Use diagrams for workflow and architecture.

• Highlight UX for AI: Specifically detail how you designed for user trust, transparency, and control in AI interactions. Use mockups, wireframes, or user flow diagrams.

• Quantify Achievements: Whenever possible, use metrics to demonstrate the impact of your work (e.g., "reduced task completion time by X%", "increased user adoption by Y%", "improved AI confidence scores by Z%").

• Be Prepared to Demo: Have links or code repositories ready (if permissible) and be ready to walk through your projects verbally.

Challenge Preparation:

• System Design: Practice designing scalable, resilient, and trustworthy AI systems. Consider trade-offs between different architectural choices.

• Coding Challenges: Brush up on Python/TypeScript data structures, algorithms, and common design patterns. Be ready for problems related to API interactions or data processing.

• AI/UX Scenarios: Prepare to discuss how you would design an AI agent for a specific business problem at RBC, focusing on user interaction and trust mechanisms.

• Behavioral Questions: Use the STAR method (Situation, Task, Action, Result) to prepare answers for questions about teamwork, problem-solving, and handling challenges.

📝 Enhancement Note: The interview process is likely to be rigorous, reflecting RBC's position as a major financial institution. A strong portfolio that vividly demonstrates practical application of AI and UX principles, alongside solid technical and behavioral interview preparation, will be key to success.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python, TypeScript (primary focus).

• Backend Frameworks: Likely frameworks like Flask, FastAPI (Python) or Node.js/Express (TypeScript).

• Frontend Frameworks: Modern JavaScript frameworks such as React, Angular, or Vue.js for building user interfaces.

• AI/ML Libraries: Libraries such as TensorFlow, PyTorch, Scikit-learn, Hugging Face Transformers, LangChain, or similar for developing and integrating AI models and agentic capabilities.

• API Development: Experience with RESTful API design and implementation, potentially GraphQL and SOAP for enterprise integrations.

Analytics & Reporting:

• Data Visualization Tools: Tools like Tableau, Power BI, or custom dashboards built with frontend libraries for monitoring AI performance and user engagement.

• Logging & Monitoring: Tools for tracking system health, API performance, and AI model behavior in production.

CRM & Automation:

• Enterprise Systems: Familiarity with integrating with core corporate platforms such as project management tools (e.g., Jira), collaboration suites (e.g., Microsoft Teams, Slack), source control (e.g., Git/GitHub/GitLab), and enterprise resource planning (ERP) systems.

• Integration Platforms: Experience with middleware or integration platforms if applicable for complex enterprise connectivity.

📝 Enhancement Note: The technology stack emphasizes a full-stack approach with a strong AI/ML component. Proficiency in Python and TypeScript is fundamental, along with experience in modern frontend development and API integrations. Familiarity with AI orchestration frameworks like LangChain or similar is highly relevant given the "agentic" nature of the role.

👥 Team Culture & Values

Operations Values:

• Client First: All AI solutions must ultimately serve the needs of RBC's clients, directly or indirectly, ensuring value creation and trust.

• Integrity: Upholding ethical standards in AI development, ensuring fairness, transparency, and compliance with regulations.

• Collaboration: Working effectively across diverse teams (engineering, product, UX, business) to achieve shared goals.

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

• Excellence: Striving for high-quality solutions, continuous improvement, and measurable impact in all AI initiatives.

Collaboration Style:

• Cross-functional Integration: The role requires seamless collaboration with platform engineering, UX design, product management, and business analysts to translate requirements into functional AI experiences.

• Process Review Culture: An environment where workflows and AI implementations are regularly reviewed, critiqued, and iterated upon to ensure optimal performance and user satisfaction.

• Knowledge Sharing: Encouraging the sharing of best practices, learnings from AI experiments, and insights into human-agent interaction patterns across the team and broader organization.

📝 Enhancement Note: RBC's stated values are deeply embedded in its culture. For an AI Engineer, this means approaching development with a strong sense of responsibility, focusing on building AI that is not only technically advanced but also ethical, reliable, and beneficial to clients and the organization.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Autonomy and Control: Designing AI agents that are sufficiently autonomous to be useful but also provide users with clear control and understanding to build trust.

• Navigating Regulatory Landscape: Developing AI solutions within a heavily regulated financial services environment requires strict adherence to governance, compliance, and risk management protocols.

• Scalability and Integration: Ensuring AI capabilities can scale across a large enterprise and integrate seamlessly with a complex ecosystem of existing corporate systems.

• User Adoption: Convincing users, particularly those less familiar with AI, to adopt and trust new AI-driven tools and workflows.

Learning & Development Opportunities:

• AI Specialization: Opportunities to become an expert in cutting-edge areas of AI, such as advanced agent architectures, reinforcement learning for agents, and sophisticated UX for AI.

• Industry Conferences & Certifications: Support for attending relevant AI and technology conferences and pursuing certifications to stay abreast of industry trends.

• Mentorship Programs: Access to mentorship from senior AI leaders and experienced engineers within RBC, fostering career development and skill enhancement.

• Internal Training: RBC offers extensive training programs, including specialized tracks in financial services technology and AI, to support continuous learning.

📝 Enhancement Note: The challenges presented are inherent to deploying advanced AI in a large, regulated enterprise. Successfully navigating these will offer significant professional growth. The learning opportunities are substantial, positioning this role as a significant step in an AI engineering career, especially within the financial sector.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex workflow you automated using AI. What were the key challenges in designing the human-AI interaction for this workflow?" (Focus on progressive autonomy, trust, and explainability).

• "How would you design an AI agent to assist RBC clients with [specific banking task, e.g., complex loan inquiries]? What trust mechanisms would you implement?" (Assess understanding of AI UX in a financial context).

• "Walk us through your process for building and deploying an AI-driven feature from ideation to production. How do you ensure quality and user adoption?" (Evaluate lifecycle management and impact orientation). Company & Culture Questions:

• "How do you ensure your AI development aligns with principles of integrity and client-first, especially in a regulated industry like banking?" (Gauge understanding of RBC's values).

• "Describe a time you had to collaborate with non-technical stakeholders to explain a complex AI concept or feature. How did you ensure they understood and trusted the solution?" (Assess communication and collaboration skills).

• "How would you measure the success and impact of an AI agentic UX feature within RBC?" (Focus on metrics, ROI, and operational improvements). Portfolio Presentation Strategy:

• Storytelling: Frame your portfolio projects as narratives, highlighting the problem, your innovative solution, and the positive outcomes.

• Visual Aids: Use clear diagrams, mockups, and concise code snippets (if appropriate) to illustrate your technical and design decisions.

• Focus on Impact: Emphasize how your work delivered tangible business value, improved user experience, or solved complex operational challenges.

• Address AI Specifics: For each project, clearly articulate your role in designing the AI components, the prompt engineering involved, and the specific UX considerations for human-AI interaction.

📝 Enhancement Note: Interview preparation should focus on demonstrating a strong grasp of AI principles, full-stack development, and user-centric design, all within the context of financial services. Candidates should be ready to articulate their thought process, problem-solving skills, and ability to build trustworthy AI solutions.

📌 Application Steps

To apply for this AI Engineer position:

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

• Customize Your Resume: Tailor your resume to highlight experience with Python, TypeScript, full-stack development, AI/ML, prompt engineering, agentic AI patterns, and enterprise API integrations. Quantify achievements wherever possible.

• Prepare Your Portfolio: Curate 2-3 key projects that best demonstrate your full-stack AI-driven development and agentic UX design skills. Be ready to present them with a clear narrative of problem, solution, and impact.

• Research RBC's AI Strategy: Understand RBC's stated values and their approach to technology and client service. Consider how your skills can contribute to their goals in AI adoption and innovation.

• Practice Interview Questions: Prepare to answer technical, behavioral, and system design questions, focusing on your ability to build trustworthy, scalable, and user-friendly AI experiences. Rehearse your portfolio presentation.

⚠️ 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.