Principal AI DevSecOps Engineer

Key Skills

Aartificial intelligence, Continuous Integration & Continuous Delivery - CI/CD, DevSecOps, Effective communication skills, HuggingFace, Machine learning techniques, PyTorch, TensorFlow, Terraform

Job Description

What's the opportunity?

At RBC, you'll be joining a team of leading platform engineers and security specialists focused on implementing and optimizing our enterprise GenAI platform infrastructure. You will have access to cutting-edge GPU technologies, multi-cloud environments, and the computational resources to support novel AI/ML workload deployment alongside traditional enterprise applications.

We're looking for an exceptional Principal AI DevSecOps Engineer who's excited by the opportunity of being at the forefront of implementing secure, scalable infrastructure for next-generation AI applications and mission-critical enterprise systems. As a Principal AI DevSecOps Engineer, you'll be part of a collaborative group who aims to deliver end-to-end platform solutions – everything from Kubernetes cluster management and GPU optimization, to implementing enterprise-grade security frameworks, to deploying complex multi-cloud architectures. The goal is to understand the needs of our AI control plane team and platform architects and bring to life secure and efficient solutions that can only be achieved through deep expertise in both traditional application deployment and AI/ML workload management.

Your responsibilities include:

• AI/ML Platform Implementation: Executing deployment and management of GenAI platform components, implementing end-to-end ML model deployment pipelines, and optimizing GPU cluster management across Kubernetes environments;

• Enterprise Application & Infrastructure Operations: Building and maintaining highly available Kubernetes clusters for both traditional applications and GPU-intensive AI workloads, implementing advanced Kubernetes features, and managing multi-tenant environments;

• Multi-Cloud Platform Deployment: Deploying solutions across AWS SageMaker, Azure Machine Learning, and integrating OpenShift Container Platform with cloud-native AI services;

• Advanced Security & Networking Implementation: Designing comprehensive security controls across AI/ML pipelines, deploying advanced networking solutions including service mesh and network segmentation, and ensuring compliance with enterprise security policies;

• Platform Engineering & Automation: Building Infrastructure as Code for diverse platform components, developing automation tools for platform management, and implementing self-service capabilities for development teams; and

• Troubleshooting and Support: Resolving complex infrastructure issues across diverse application portfolios and maintaining comprehensive monitoring and alerting systems.

You're our ideal candidate if you have:

• 8+ years of hands-on experience with Kubernetes in production environments and 5+ years of experience with AI/ML infrastructure and model deployment;

• Expert-level knowledge of AWS SageMaker, Azure Machine Learning, and extensive experience with OpenShift Container Platform (OCP);

• Programming expertise in Python, Go, Bash, and Infrastructure as Code tools (Terraform, Helm, Kustomize);

• Advanced Kubernetes networking knowledge including CNI plugins, network policies, and service mesh implementations (Istio, Linkerd);

• Deep understanding of enterprise security frameworks including container security, vulnerability scanning, secrets management, and compliance standards (SOC2, PCI-DSS, GDPR);

• Experience with ML frameworks (TensorFlow, PyTorch, Hugging Face) and MLOps tools (MLflow, Kubeflow, Seldon, KServe);

• Proven experience managing GPU clusters, NVIDIA GPU Operator, and distributed training environments;

• Knowledge of professional software engineering best practices including GitOps methodologies, CI/CD pipeline implementation, and infrastructure automation; and

• Strong communication skills, collaborative attitude, and comfort working in complex multi-platform environments.

What's in it for you?

• Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;

• Leaders who support your development through coaching and managing opportunities;

• Ability to make a difference and lasting impact from a local-to-global scale.

About RBC Borealis

RBC Borealis is the driving force behind Royal Bank of Canada’s AI and data innovation. As part of Canada’s largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we’re at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.

Inclusion and Equal Opportunity Employment

RBC is an equal opportunity employer committed to diversity and inclusion. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status or any other legally-protected factors. Disability-related accommodations during the application process are available upon request.