Senior Release Engineer

Questrade Financial Group•Toronto, ON

5d•CA$120,000 - CA$140,000•Hybrid

About The Position

This is a high-impact, hybrid release engineering role bridging global enterprise platform standards with the specialized technical needs of our high-speed brokerage systems. You will own, optimize, and modernize our CI/CD pipelines across a polyglot codebase—ranging from low-latency native C++ (Linux) microservices to Angular Micro-Frontends, .NET Core, Node.js, Python, and Apigee API gateways on GCP. Your mission is to eliminate build friction, accelerate compilation and feedback loops, embed modern AI SDLC and DevSecOps tooling, and ensure safe, automated releases for active trading systems.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or a related quantitative engineering field (or equivalent practical experience).
5+ years of software/DevOps engineering experience, with 3+ years dedicated to release engineering, CI/CD pipeline development, and build optimization.
Advanced expertise in configuring and maintaining pipelines in GitLab CI, CircleCI, or Jenkins.
Hands-on experience with Google Cloud Platform (GCP) (Cloud Build, Artifact Registry, GKE, Cloud Run, Cloud Storage, Cloud CDN).
Deep familiarity with build systems across compiled languages (C++ gcc/clang, C# .NET) and web/scripting stacks (Node.js, Python, Angular MFEs).
Demonstrated experience automating deployment and lifecycle workflows for Apigee API Gateway or similar API routing platforms.
Strong proficiency in Python, Bash, or Go for developing custom CLI automation tools and pipeline extensions.
Proficient with Terraform, Docker image optimization, layer caching, and container scanning.
Experience integrating automated test dashboards, SAST/DAST tools (SonarQube/Snyk), and modern AI PR tools (CodeRabbit).
Strong analytical and problem-solving skills with a developer-first mindset focused on improving developer velocity and platform safety.

Responsibilities

Architect, standardize, and maintain modular CI/CD pipelines using GitLab CI / CircleCI / Jenkins tailored for high-throughput brokerage applications.
Implement advanced build caching (cache, distributed compilation, multi-stage Docker builds) to drastically cut compile times for native C++ (Linux) backend services.
Standardize dependency management and artifact publishing for C#, Node.js, and Python microservices into GCP Artifact Registry.
Build reusable pipeline templates to empower developer self-service while maintaining team-wide quality gates.
Design and execute independent release pipelines for Angular Micro-Frontends, enabling modular feature deployments without monolithic application rebuilds.
Automate deployment workflows to GCP Cloud Storage and Cloud CDN, managing dynamic version manifest updates and edge cache invalidation.
Automate the complete lifecycle of Apigee API proxy bundles, including linting (apigeelint), automated integration testing, and promotion across Dev, Staging, and Production environments.
Coordinate deployment dependencies between Apigee API routing and backend microservices deployed on GKE (Google Kubernetes Engine) or Cloud Run.
Maintain Infrastructure as Code (Terraform) configurations associated with release triggers, pipeline execution roles, and environment provisioning.
Integrate AI-assisted code review tools (e.g., CodeRabbit, automated PR review bots) directly into code review workflows to accelerate PR throughput.
Embed automated static analysis (SAST) and dynamic security testing (DAST) tools (e.g., SonarQube, Snyk, Semgrep) into pull request checks.
Aggregate and parse unit/E2E test outputs (JUnit, Cypress, Playwright) to publish visual feedback directly into PR summaries and engineering dashboards.
Partner closely with the Enterprise Platform Team to adopt core global infrastructure, security baselines, and IAM policies while tailoring execution for brokerage needs.
Automate domain-specific release gating requirements, including financial compliance controls, change logs, and audit trails.
Track and continuously improve core DORA metrics (Deployment Frequency, Lead Time for Changes, Change Failure Rate, MTTR).