Global leader in data center and interconnection services, enabling digital transformation.
Design and develop scalable microservices and APIs for enterprise SaaS platform.
4 days ago ago
C$131,000 - C$181,000
Expert & Leadership (13+ years)
Full Time
Toronto, Ontario, Canada
Office Full-Time
Company Size
10,000 Employees
Service Specialisms
Data center colocation
Interconnection services
Smart Hands / remote support
Software-defined interconnection
Network Edge services
Equinix Metal (bare metal)
Equinix Fabric (cloud routing)
Managed services (integration & advisory)
Sector Specialisms
No specialisms available
Role
Description
ai ops
api development
automated testing
devsecops
microservices
continuous delivery
Partner with product managers to translate business intent into technical outcomes that scale globally
Participate in “AI Ops” automation across environments for faster root cause analysis and proactive reliability improvements
Advocate for pragmatic innovation—balancing long-term platform health with short-term delivery needs
Stay curious, experiment with emerging technologies, and continuously raise the engineering bar
Influence cross-functional architecture decisions for customer, billing, pricing, and commerce systems integrated across the Quote-to-Cash flow
Develop reusable frameworks and self-service platforms for onboarding, configuration, and lifecycle management
Establish best practices for API-first development, automated testing, DevSecOps, and continuous delivery
Participate in the technical strategy for modular, event-driven, and scalable microservices that power enterprise-grade workflows
Champion design principles that balance innovation, maintainability, observability, and operational excellence
Operate as a “system thinker” – simplifying complexity across architecture, teams, and tools
Apply AI tools to accelerate software design, development, and operations - e.g., AI-assisted architecture reviews, test generation, and defect prediction
Serve as a mentor and technical coach, raising the level of engineering maturity across teams
Lead by example—building reliable, secure, and observable systems with strong performance SLAs
Requirements
cs degree
8+ years
distributed systems
microservices
generative ai
kafka
Bachelor’s or Master’s degree in Computer Science and Engineering or equivalent
Experience in enterprise application integration (ERP, CRM, CPQ, or billing systems) and Quote-to-Cash automation will be a plus
8+ years of engineering experience with strong depth in distributed systems, API platforms, and cloud-native development (Java, Node.js, or equivalent)
Excellent communication skills; able to influence at multiple levels of the organization
Proven experience in designing and operating microservice architecture at scale (preferably multi-tenant SaaS/PaaS)
Hands-on experience applying AI in software engineering—e.g., using generative AI for design, code, or operational insights
Strong knowledge of event streaming (Kafka, Pub/Sub), container orchestration, automated CI/CD and observability frameworks (Prometheus, OpenTelemetry, Grafana, etc.)
Deep understanding of data modeling, domain-driven design, and API lifecycle management