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Director & Principal Engineer, AI​/ML & MLOps Platform

Job in Vancouver, BC, Canada
Listing for: RBC
Full Time position
Listed on 2026-08-04
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 240000 CAD Yearly CAD 180000.00 240000.00 YEAR
Job Description & How to Apply Below

What is the opportunity?

Global Functions Technology (GFT) is part of RBC’s Technology and Operations division. GFT’s impact is far-reaching as we collaborate with partners from across the company to deliver innovative and transformative IT solutions. Our clients represent Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking and Wealth Management. We also lead the development of digital tools and platforms to enhance collaboration.

In your role, You’ll architect and create systems that directly influence billions in lending decisions, shaping RBC’s competitive edge in financial innovation.

Job Description

We’re seeking a Director & Principal Engineer, AI/ML & MLOps Platform, who brings a unique blend of deep technical expertise and strategic leadership. This is a hands‑on engineering leadership role focused on building and scaling data‑driven systems and platform capabilities that enable advanced analytics, machine learning, and impactful business decisions. You will play a key role in shaping our next‑generation credit decisioning and risk management platform, and lead by example in applying sound architectural thinking, engineering rigor, and technical mentorship.

You will manage a team of seasoned engineers to deliver the visions to scale your impacts and pace of development.

What will you do?
  • Lead by Doing:
    Design, build, and review scalable data pipelines, analytics platforms, and ML systems. This is a hands‑on role with end‑to‑end ownership, balancing hands‑on coding (20‑30%) with solution architectural & engineering leadership.
  • Set Technical Direction:
    Define and promote best practices in data and ML engineering. Evaluate emerging technologies and guide adoption to drive innovation.
  • Partner Cross‑Functionally:
    Work closely with data scientists, business leaders, and IT teams to understand needs and translate them into technical solutions. Your first set of prominent goals are to transform the bank’s retail credit decisioning by bringing together a set of platform capabilities to enable our risk experts to scale vertically and horizontally to provide the depth and the breadth for competitive and personalize lending products.
  • Mentor and Inspire:
    Coach engineers and foster a high‑performing, collaborative culture. Champion engineering excellence and team growth. You are not an old fashioned manager that just command, but a role model that cultivates a culture of innovation and high performance, who skillfully inspires the next generation of leaders without micro managing.
  • Deliver at Scale:
    Ensure projects are executed with high quality, on time, and aligned with business goals. Proactively identify risks and enforce compliance standards, especially around data governance and security.
What do you need to succeed? Must Have:
  • 8+ years of experience in designing and building data‑intensive applications, with 3+ years in a senior technical leadership role.
  • Deep expertise in modern distributed data processing and ML engineering tools and languages (e.g., Python, Java/Scala, PySpark/Spark, Kafka, SQL, orchestration frameworks).
  • Strong understanding of the ML lifecycle and MLOps practices, including model deployment, monitoring, and CI/CD pipelines. Experience with real‑time inference systems in both on‑prem and Cloud.
  • Proven experience in cloud platforms like AWS or Azure, with knowledge of scalable architecture patterns, and proficient in IaC (SDK, Terraform)
  • Excellent communication skills - able to clearly explain complex technical concepts to both technical and non‑technical audiences.
  • Demonstrated success in leading engineering teams and delivering high‑impact platforms or products.
  • Bachelor's degree in Computer Science, Engineering, or a related field;
    Master's or PhD preferred.
Nice to Have:
  • Hands‑on experience with AWS Sage Maker and related services (Glue, EMR, Lambda, Step Functions, Airflow, Cloud Watch).
  • Track record of building high‑performing teams (e.g., hiring/retaining top talent, improving team NPS)
  • Background in enterprise‑level data governance, privacy, and security practices.
What’s In For You?

We thrive on the challenge to be our…

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