Responsibilities
- Develop and lead the strategic direction of DevOps practices across multiple cloud environments and regions
- Design and manage large-scale Kubernetes platforms and container-based infrastructure
- Lead the implementation and governance of infrastructure as code across all deployment environments
- Drive DevSecOps initiatives, including identity and access management, compliance, secrets management, auditing, and zero-trust security models
- Ensure high reliability, performance service-level agreements, and cost efficiency in production systems
- Lead large-scale cloud migration projects and modernization of legacy platforms
- Define and manage observability frameworks and practices to ensure production system stability
- Design and operate infrastructure for AI/ML platforms, including model deployment, GPU workload management, LLM gateways, vector databases, and CI/CD pipelines
- Integrate AI-powered development tools such as Claude and Cursor into daily workflows to enhance productivity and output quality
- Collaborate with engineering, product, and executive teams to align platform development with business objectives
- Articulate complex technical infrastructure decisions and trade-offs to both technical and non-technical audiences
- Lead technical design reviews, architectural planning sessions, and readiness evaluations for system releases
- Define and enforce platform engineering standards and best practices across client engagements
- Provide guidance and mentorship to early- and mid-career engineers to improve technical skills and project impact
- Serve as the escalation point for difficult infrastructure and platform-related technical issues
- Assess new technologies and tools, proposing adoption patterns that enhance system reliability and developer experience
Work Arrangement
Remote (Country) — Canada
Other
This is a 4 month contract assignment with potential to extend
