Senior Software Engineer

RBC•Toronto, ON

20d•Onsite

About The Position

We're looking for a visionary Senior Software Engineer to provide strategic technical leadership and deep subject-matter expertise in designing and implementing enterprise-scale AI services. This is an exceptional opportunity to shape the future of AI engineering at RBC, mentoring a team of talented engineers while driving architectural excellence and innovation across our production AI infrastructure.

Requirements

5+ years of software engineering experience, with significant expertise designing and implementing distributed systems and AI service architectures
Proven track record architecting and delivering large-scale, production systems serving millions of transactions or requests
Advanced expertise in software engineering best practices, architectural patterns, design reviews, and system optimization
Deep hands-on experience designing microservices, event-driven, and service-oriented architectures at enterprise scale
Expert-level proficiency in Python and Golang, with ability to make principled technology choices
Demonstrated leadership mentoring engineers and influencing technical direction across teams
In-depth knowledge of containerization and orchestration platforms (Docker, Kubernetes, OCP4) with production deployment experience
Advanced experience optimizing performance at scale, implementing sophisticated caching strategies, and tuning complex distributed systems
Hands-on expertise building and deploying applications across hybrid cloud environments (AWS, Azure) and on-premise infrastructure
Expert-level knowledge of data architecture, database design (SQL and NoSQL), and data access patterns in high-scale environments
Understanding of ML model serving, inference optimization, advanced ML system design patterns, and MLOps
Experience designing and implementing infrastructure for agentic AI systems and self-hosted ML model deployment
Advanced expertise in observability, monitoring, logging, and security practices for distributed systems

Nice To Haves

Agentic AI
Application Performance Management (APM)
CI/CD
Domain Driven Design (DDD)
Event Driven Architecture (EDA)
Kubernetes
Model Deployment
Model Evaluation
Non Relational Databases
Python (Programming Language)
SQL Databases
Systems Architecture

Responsibilities

Defining technical vision and strategy for AI services architecture, ensuring alignment with business objectives and enterprise standards
Designing, building, and optimizing mission-critical AI services that power the organization's most strategic AI and ML applications
Establishing and evangelizing software best practices, architectural patterns, and quality standards across AI engineering teams
Leading complex technical design decisions and enterprise-scale system architecture for AI platforms, including API frameworks, data governance models, and integration patterns
Collaborating cross-functionally with infrastructure, platform, and ML teams to architect seamless, reliable, and performant AI systems at scale
Mentoring and developing junior and staff engineers, fostering a culture of technical excellence and continuous learning
Building highly scalable, resilient, and secure cloud and on-premise software systems for hosting AI services using cutting-edge technologies
Driving technical innovation and evaluating emerging technologies to maintain competitive advantage