Lead AI/ML Engineer

RBC; Toronto; On-site; CAD 140,000 - 230,000; Full time

Benefits offered by this job

Bonuses

Flexible benefits

Stock options where applicable

Job summary

RBC is seeking a founding member for its Site Reliability Engineering team to build the bank’s first-ever Agentic AI platform for software reliability and resiliency. You will design end-to-end AI-driven solutions, develop intelligent automation frameworks, and implement production-grade infrastructure at enterprise scale.

The role emphasizes cutting-edge AI at scale, incident prevention, and reducing toil while collaborating with cross-functional teams.

Qualifications

• 5 years hands-on ML engineering experience in production
• Expertise in Agentic AI frameworks/tools (LangChain, LangGraph, AutoGen, CrewAI) for autonomous systems
• Deep understanding of Model Context Protocol (MCP) for AI agents
• Experience building AI agents with tool-calling, memory, and reasoning
• Proficiency in Python and ML libraries (scikit-learn, TensorFlow, PyTorch)
• Knowledge of containers (Docker), orchestration (Kubernetes/OpenShift), and IaC (Ansible, Terraform)
• Ability to translate technical concepts into business value and collaborate cross-functionally

Responsibilities

• Design end-to-end Agentic AI solutions that autonomously detect and resolve incidents
• Develop intelligent automation frameworks using LangChain and LangGraph
• Build ML-powered monitoring and alerting to reduce false positives and improve MTTR/MTTI
• Architect scalable production-grade solutions on OpenShift and Kubernetes
• Implement IaC with Ansible and containerization (Docker) for reproducible deployments
• Collaborate with incident management to turn pain points into AI-driven automation
• Lead design discussions and contribute to RBC’s AI-powered reliability strategy

Skills

Python

ML engineering

Agentic AI

Model Context Protocol

Multi-agent systems

Tools

Docker

Kubernetes/OpenShift

Ansible

Terraform

LangChain

LangGraph

Job description

Job Description

WHAT IS THE OPPORTUNITY?

Join RBC’s Site Reliability Engineering team as a founding member building the bank’s first-ever Agentic AI platform for Software reliability and resiliency. You’ll pioneer intelligent automation systems that autonomously prevent incidents, accelerate response times, and transform how we maintain resilience across enterprise systems. This is a rare opportunity to shape the future of AI-driven reliability at scale. Your innovations will protect millions of daily customer transactions and sign-ins. With a clear technical leadership trajectory, you’ll architect cutting-edge solutions at the intersection of AI and infrastructure, setting the standard for autonomous operations in financial services.

WHAT WILL YOU DO?

• Design and implement end-to-end Agentic AI solutions that autonomously detect anomalies, identify root causes, and resolve incidents with minimal human intervention

• Develop intelligent automation frameworks using LangChain and LangGraph to create context-aware agents that learn from incident patterns and continuously improve response strategies

• Build ML-powered monitoring and alerting systems that distinguish signal from noise, dramatically reducing false positives and improving MTTD (Mean Time to Detect) and MTTI (Mean Time to Identify)

• Architect scalable, production-grade solutions on OpenShift and Kubernetes that process real-time system metrics and telemetry data at enterprise scale

• Implement infrastructure-as-code using Ansible and containerization (Docker) to ensure reproducibility, consistency, and rapid deployment across environments

• Partner with incident management and operations teams to translate operational pain points into AI-driven automation opportunities that measurably reduce toil

• Establish and track KPIs focused on reducing MTTR (Mean Time to Resolve), MTTD, and MTTI while improving system reliability

• Lead technical design discussions and contribute to architectural decisions that shape RBC’s AI-powered reliability strategy

WHAT DO YOU NEED TO SUCCEED?

Must have:

• Strong 5 years hands on ML engineering experience with designing, training, and deploying machine learning models in production environments
• Proven expertise in Agentic AI frameworks and tools (LangChain, LangGraph, AutoGen, CrewAI, or similar) and building autonomous, multi-agent systems
• Deep understanding of Model Context Protocol (MCP) for enabling AI agents to interact with external systems and data sources
• Experience building AI agents with tool-calling capabilities, memory management, and reasoning chains
• Proficiency in Python and experience with ML libraries (scikit-learn, TensorFlow, PyTorch, or similar)
• Working knowledge of containerization (Docker), orchestration (Kubernetes/OpenShift), and infrastructure-as-code principles (Ansible, Terraform)
• Demonstrated ability to translate complex technical concepts into business value and collaborate effectively with cross-functional teams

Nice-to-have:

• Prior experience in Site Reliability Engineering, DevOps, or infrastructure monitoring roles
• Familiarity with observability tools (Prometheus, Grafana, ELK stack) and incident management platforms (PagerDuty, ServiceNow)
• Experience with LLMs, prompt engineering, and retrieval-augmented generation (RAG) architectures
• Background in financial services or other highly regulated industries with strict reliability requirements

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

#LI-POST

#TECHPJ

Job Skills

Docker Kubernetes Architecture, LangChain (FrameWork), LangGraph, Machine Learning (ML), Python (Programming Language), Red Hat Ansible, Red Hat OpenShift

Additional Job Details

Address

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City

Toronto

Country

Canada

Work hours/week

37.5

Employment Type

Full time

Platform

TECHNOLOGY AND OPERATIONS

Job Type

Regular

Pay Type

Salaried

Posted Date

2026-04-27

Application Deadline

2026-08-21

Note

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

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One 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.