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Associate Director, Data & AI Platform Engineer

RBC

Toronto

On-site

CAD 80,000 - 100,000

Full time

Today
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Job summary

A leading financial institution in Toronto seeks a hands-on Data & AI Platform Engineer to advance capabilities powering Research Digitization and Banking solutions. Candidates should have strong skills in Python, SQL, Databricks, and Kubernetes, with experience in data engineering and machine learning. Opportunities for professional growth and a flexible work environment are offered.

Benefits

Comprehensive Total Rewards Program
Flexible work/life balance options
World-class training program in financial services

Qualifications

  • Solid understanding of Hybrid Data & AI platforms
  • 2+ Years experience with Databricks
  • Hands-on experience in Data Engineering and applied Machine Learning
  • Deep understanding of database systems and distributed computing
  • Experience building, scaling, managing, and monitoring ML pipelines
  • Proficient in CI/CD principles

Responsibilities

  • Engineer advanced Data & AI capabilities for Banking and Global Market solutions
  • Evaluate and adopt AI Observability & Monitoring solutions
  • Deploy and manage containerized applications using Kubernetes
  • Provide expertise in distributed and parallel computing
  • Automate AI infrastructure provisioning

Skills

Databricks
Data Engineering
Machine Learning
Python
SQL
Kubernetes
ML Flow
Spark
Terraform

Education

Degree in Computer Science or Engineering
Job description
Overview

What is the opportunity?

Capital Markets Quantitative & Technology Services - Data AI and Research Technology (DART) team is hiring a hands-on Data & AI Platform Engineer to advance Data & AI capabilities that power Research Digitization, Banking and Global Market solutions.

What will you do?
  • Engineer advanced Data & AI capabilities to power Research Digitization, Banking and Global Market solutions
  • Evaluation and subsequent adoption of AI Observability & Monitoring solutions, Vector databases, inference engines and other technologies in the AI ecosystem
  • Deploy, manage, performance tune and scale containerized applications using Kubernetes. Architect clusters leveraging fit-for-purpose hardware for AI workloads
  • Provide subject matter expertise in distributed and parallel computing. Analyze ML and data processing workloads to identify latency contributors, inefficient compute utilization and provide remediation recommendations
  • Automate AI infrastructure provisioning
  • Create reports for AI infrastructure usage and cost reports
  • Collaborate with Enterprise Architecture, Data & AI governance teams to ensure full alignment of platform with enterprise data strategy, AI governance frameworks, security policies, compliance and architecture standards
  • Present platform architecture artifacts to technical and non-technical stakeholders
What do you need to succeed?

Must Have

  • Solid understanding of Hybrid Data & AI platforms with emphasis on security, access control compute/storage architecture, AI workloads, cost visibility, monitoring and DevOps enablement
  • 2+ Years experience with Databricks
  • Hands on experience in Data Engineering and applied Machine Learning
  • Deep understanding of database systems and distributed computing
  • Experience building, scaling, managing and monitoring ML pipelines
  • Strong Proficiency in Python, SQL, Kubernetes, ML Flow and Spark
  • Proficient in CI/CD principles, version control and best practices for deploying AI workloads to production
  • Experience with Terraform

Nice to Have

  • Good understanding of Classic ML Principles and Generative AI
  • Working experience with LLMs, Agents
  • Degree in Computer Science or Engineering
What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
  • Leaders who support your development through coaching and managing opportunities
  • Ability to make a difference and lasting impact
  • Work in a dynamic, collaborative, progressive, and high-performing team
  • A world-class training program in financial services
  • Flexible work/life balance options
  • Opportunities to do challenging work
  • Opportunities to take on progressively greater accountabilities
  • Access to a variety of job opportunities across business and geographies

#LI-POST

Job Skills

Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements Analysis

Additional Job Details

Address: RBC CENTRE, 155 WELLINGTON ST W:TORONTO

City: Toronto

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: CAPITAL MARKETS

Job Type: Regular

Pay Type: Salaried

Posted Date: 2025-09-16

Application Deadline: 2025-09-30

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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