Staff Software Engineer

RBC•Calgary, AB

19d•Onsite

About The Position

We're looking for an experienced Staff Software Engineer who will bring focus and subject-matter expertise around designing and implementing robust, scalable AI services. This is a unique opportunity to grow in the world of AI engineering and work with a team of passionate individuals committed to delivering enterprise grade software solutions for our production AI services.

Requirements

Strong and relevant experience designing and implementing distributed systems and software architectures for AI services
Proven expertise in software engineering practices, including code review, testing, design patterns, and software architecture
Hands-on experience building and deploying scalable applications and services using modern frameworks and technologies
In-depth knowledge of containerization technologies such as Docker and Kubernetes or OpenShift Container Platform (OCP4)
Experience designing and implementing APIs, event-driven, microservices, and service-oriented architectures
Strong proficiency in Python and Golang
Experience optimizing application performance, implementing caching strategies, and tuning distributed systems
Hands-on experience building and deploying applications across hybrid environments on-prem and major cloud environments, such as AWS and Azure
Experience designing data access layers and working with databases (both SQL and NoSQL such as MongoDB) in production environments
Understanding of machine learning model serving, inference optimization, and ML system design patterns
Experience designing and building infrastructure for deploying and managing agentic workflow systems and self-hosted ML models
Experience with observability, monitoring, and logging practices to ensure visibility into system behaviour and performance

Responsibilities

Designing, building, and optimizing AI services that power the business’ AI and ML applications
Architecting and implementing software best practices and standards for code quality, performance, and scalability across AI applications
Collaborating with infrastructure engineers and machine learning researchers to ensure seamless integration, reliability, and performance of AI applications at scale
Leading technical design decisions and system architecture for AI applications and projects, including API design, data models, and integration patterns
Building highly scalable, resilient cloud and on-premises software systems for hosting AI services using state-of-the-art technologies