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Principal Data Science and AI Engineer

Job in Toronto, Ontario, M5A, Canada
Listing for: 0000050007 Royal Bank of Canada
Full Time position
Listed on 2026-10-09
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software)
Job Description & How to Apply Below

Job Description

What is the opportunity?

Are you ready to lead transformative AI initiatives and drive innovation at enterprise scale? Do you excel in environments of rapid technological advancement and thrive on solving complex, high-impact challenges? Are you passionate about shaping the future of businesses through cutting-edge AI solutions and influencing organizational strategy?

As a Principal AI Engineer, you will be at the helm of developing, deploying, and owning the strategic direction of advanced AI systems, including autonomous AI agents that leverage and fine-tune large language models (LLMs) and other deep learning technologies.

This role offers a unique opportunity to define the technical roadmap, drive enterprise-wide adoption, and lead the design and implementation of intelligent systems that redefine how we operate and deliver value. You will provide technical leadership across multiple squads and domains, advise senior leadership on AI strategy and investment priorities, and be accountable for the measurable business impact of AI platform capabilities.

This is your chance to engage with state-of-the-art AI technologies, influence organizational direction at the executive level, and make a lasting impact on the industry.

This role is designed for a visionary technical leader who is passionate about advancing AI technologies and driving meaningful, measurable change. If you are ready to take on this challenge, we invite you to join us and shape the future of AI and Advice Center t will you do?

Lead the Design and Development of Platform Services for Autonomous AI Agents
  • Engineer, design, and enable the development of platform services that enable autonomous AI agents to interact with infrastructure systems like Open Shift, SQL Server, Apigee, Kafka, Elasticsearch, etc.

  • Design APIs and natural language interfaces for AI agents to perform tasks like diagnostics, remediation, and maintenance.

  • Integrate data (Metrics, Events, Logs, Traces) to power AI-driven anomaly detection and automation.

  • Drive AI experiments from proof-of-concept through production deployment, establishing LLMOps practices, model governance, and lifecycle management frameworks.

  • Strategic Ownership and Roadmap
  • Define and own the 12–18 month technical roadmap for AI platform services, aligning with organizational priorities and business objectives.

  • Evaluate build-vs-buy decisions for AI infrastructure components, tooling, and vendor selection.

  • Influence organizational investment priorities through technical analysis, competitive landscape assessment, and strategic recommendations.

  • Accountable for the success, adoption, and ROI of AI platform capabilities across the enterprise.

  • Define and track KPIs for AI-driven solutions, reporting outcomes to senior leadership.

  • AI-Driven Innovation to Serve Intelligent Advice Center
  • Optimize platform services for generative AI models and autonomous workflows.

  • Apply AI techniques like reinforcement learning and transfer learning to enhance Advisor and Client experience.

  • Experiment with emerging AI technologies to elevate digital channels, advisor and client interaction management and optimize client experience.

  • Establish standards for responsible AI, model governance, and ethical AI practices across the organization.

  • Provide Technical Leadership and Executive Influence
  • Lead architecture design, code reviews, and technical discussions for high-quality platform solutions.

  • Bridge platform teams and AI squads to ensure seamless integration and alignment across multiple domains.

  • Promote best practices for platform management, AI integration, and automation across teams.

  • Make high-impact technical decisions on architecture, tooling, and vendor selection with enterprise-wide implications.

  • Act as the final technical escalation point for complex AI system issues.

  • Own technical risk assessment for AI initiatives and communicate risk posture to leadership.

  • Advise senior leadership (VP+/SVP) on AI strategy, capabilities, and emerging opportunities.

  • Present to executive steering committees on technical direction, progress, and business impact.

  • Ensure Operational Excellence
  • Implement monitoring frameworks to ensure reliable AI-driven workflows at enterprise scale.

  • Address scalability and resilience challenges in advice centers integrated with AI agents.

  • Enforce security, compliance, and data privacy standards across platform operations for AC.

  • Establish SLAs and reliability targets for AI-powered systems, ensuring accountability for uptime and…

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