Senior DevOps Engineer
Location: Ontario, Canada
Experience: 10+ years preferred
About the Role
We’re looking for a Senior DevOps Engineer to take ownership of how our work ships, scales, and stays running.
This is a hands-on, high-ownership role spanning multiple client projects and technology environments. You’ll be responsible for the delivery pipelines, cloud infrastructure, reliability, observability, and security that support our enterprise software and digital solutions.
You’ll help transform fragile or manual infrastructure into automated, secure, observable, and scalable platforms. Because we increasingly work with AI-powered applications and solutions, you’ll also help design and operate infrastructure supporting modern AI workloads.
We’re looking for someone genuinely senior—an engineer who has built and operated production platforms end to end, owned reliability, responded to real production incidents, and can make sound infrastructure decisions independently.
Just as importantly, you communicate clearly, collaborate effectively with developers and technical teams, and are comfortable working directly with clients when needed.
What You’ll Do
- Own and improve CI/CD pipelines across multiple applications and client environments.
- Design, deploy, maintain, and optimize secure cloud infrastructure.
- Automate infrastructure provisioning, configuration, deployment, and operational processes.
- Improve application and infrastructure reliability, scalability, and performance.
- Implement monitoring, logging, alerting, and observability across production environments.
- Lead infrastructure troubleshooting and production incident response.
- Establish backup, disaster recovery, and business continuity practices.
- Identify infrastructure risks and proactively improve platform resilience.
- Implement and maintain infrastructure security best practices, access controls, secrets management, and vulnerability management.
- Build and maintain containerized environments and orchestration platforms.
- Support infrastructure for AI applications, APIs, data pipelines, and modern AI workloads.
- Work closely with software engineers to improve development, testing, deployment, and release processes.
- Evaluate infrastructure technologies and make pragmatic architectural recommendations.
- Document environments, processes, architecture, and operational procedures.
- Help establish DevOps standards and best practices across projects.
- Communicate technical decisions, risks, and recommendations clearly to internal teams and clients.
What We’re Looking For
- Approximately 10+ years of DevOps, infrastructure, cloud engineering, SRE, or related experience.
- Significant experience operating production systems in real-world environments.
- Strong experience with major cloud platforms such as AWS, Azure, and/or Google Cloud Platform.
- Advanced experience designing and managing CI/CD pipelines.
- Strong Infrastructure as Code experience using technologies such as Terraform.
- Experience with Docker and container orchestration technologies such as Kubernetes.
- Strong Linux and systems administration knowledge.
- Experience with monitoring, logging, alerting, and observability platforms.
- Strong understanding of networking, DNS, SSL/TLS, firewalls, load balancing, and cloud security.
- Experience implementing backup, disaster recovery, and high-availability strategies.
- Strong scripting and automation skills.
- Experience managing secrets, credentials, IAM, and secure deployment practices.
- Proven experience responding to and resolving production incidents.
- Ability to independently investigate complex infrastructure problems and make sound technical decisions.
- Strong written and verbal communication skills.
- Ability to manage priorities across multiple projects and client environments.
AI & Modern Infrastructure Experience
Experience supporting AI infrastructure is a strong asset, including:
- Deploying and operating AI-powered applications and services.
- Infrastructure supporting LLM APIs and AI integrations.
- Containerized AI workloads.
- GPU-enabled cloud infrastructure.
- Vector databases and AI data services.
- Secure management of AI APIs, models, credentials, and data.
- Scaling and monitoring AI workloads while managing infrastructure costs.
You don’t need to be a machine learning engineer, but you should be comfortable owning the infrastructure that allows AI applications to run securely and reliably in production.
The Kind of Engineer We’re Looking For
You’re someone who sees a manual deployment and wants to automate it.
You see a production environment without proper monitoring and want to make it observable.
You see a single point of failure and start thinking about resilience.
And when something goes wrong in production, you’re comfortable taking ownership, diagnosing the problem, communicating clearly, and getting the system healthy again.
We value engineers who combine deep technical capability with ownership, curiosity, pragmatism, and strong communication.
If you’re excited about leading DevOps initiatives, improving how enterprise software is delivered, and building reliable infrastructure for both traditional and AI-powered applications, we’d love to hear from you.
Pay: $100,000.00-$150,000.00 per year
Experience:
- DevOps: 10 years (preferred)
Location:
Work Location: Hybrid remote in Ontario
