Lead DevOps Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead DevOps Engineer based in Canada. Take a technical leadership role in building reliable, scalable, and secure cloud infrastructure for a modern SaaS environment. You’ll own critical DevOps capabilities across CI/CD, infrastructure automation, observability, security, and platform engineering. A major focus will be supporting core cloud platforms alongside AI, machine learning, and data workloads. You’ll work closely with Engineering, Security, NOC, and FinOps teams to improve reliability, developer velocity, and cost efficiency. The role combines hands-on engineering with technical leadership, mentoring, and ownership of operational excellence. You’ll help establish self-service platforms, automation, and engineering standards that make software delivery safer and faster. This is an opportunity to influence the architecture and evolution of a globally used SaaS platform while solving complex infrastructure challenges. Accountabilities Provide technical leadership across DevOps and platform engineering, with a particular focus on core SaaS infrastructure and AI initiatives.Own, maintain, and continuously improve CI/CD pipelines, integrating code-quality and security scanning tools such as SonarCloud and Black Duck.Configure and enforce repository and pipeline permissions to ensure reliable scanning, appropriate access controls, and effective approval and enforcement processes.Design and maintain cloud deployment automation, including auto-scaling, progressive delivery strategies such as blue/green and canary deployments, and reliable one-click rollback capabilities.Build and manage infrastructure primarily through Terraform, using Azure CLI for emergency and ad-hoc operational requirements.Deploy and operate containerized workloads using Docker across Azure Container Apps, Azure Web Apps, and Function Apps.Own critical platform services including Azure API Management, Elasticsearch, and Databricks, ensuring reliability, security, performance, and cost efficiency.Build and operate infrastructure and delivery pipelines supporting AI, machine learning, and data workloads, including model deployment, serving, data pipelines, and production monitoring.Collaborate closely with Engineering and Security teams on network and firewall changes, ensuring requests are documented, reviewed, secure, and compliant.Develop self-service platform capabilities and internal developer tooling, including standardized “golden paths” that improve developer productivity, consistency, and safety.Automate system administration activities such as provisioning, configuration, maintenance, and disaster recovery.Partner with NOC teams to implement comprehensive observability across metrics, logs, traces, and alerting, while monitoring the reliability, quality, and cost of AI and data workloads.Embed security and compliance into infrastructure and delivery processes through DevSecOps automation, auditing, controls, and tooling.Work directly with engineers on complex technical initiatives, providing subject-matter expertise, guidance, and mentorship.Partner with FinOps teams to implement cloud and AI cost-optimization initiatives.Establish and maintain business-focused KPIs and SLOs, using operational metrics to drive continuous improvement and demonstrate platform success. Requirements Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.Demonstrated experience providing technical leadership or mentoring engineers on complex, cross-functional initiatives.Strong communication and collaboration skills, with the ability to work effectively across technical disciplines and organizational levels.Proven experience building and optimizing CI/CD pipelines for Azure-based SaaS applications, including integrated code-quality and security scanning.Hands-on experience with Azure DevOps and/or GitHub Actions.Strong infrastructure-as-code experience with Terraform.Proficiency with Azure CLI for operational, troubleshooting, and emergency activities.Strong scripting capabilities in PowerShell, Bash, Python, or a comparable language.Experience deploying and operating Docker-based workloads on Azure Container Apps, Azure Web Apps, and Function Apps.Experience managing Azure platform services such as Azure API Management, Databricks, and Elasticsearch.Experience managing network and firewall configurations, including structured change-request processes.Strong knowledge of Microsoft/Windows and Linux server environments.Solid understanding of Git, version control, and Git-based development workflows.Experience working within an agile software development lifecycle.Strong understanding of security principles and secure-by-design practices.Working knowledge of Microsoft SQL Server and IIS configuration and administration.Understanding of networking technologies including switches, routers, firewalls, VPNs, VNets, and application gateways.Strong analytical and problem-solving abilities, with a demonstrated track record of improving reliability and performance.Experience supporting AI/ML or generative AI workloads in production is highly valued.Familiarity with Azure Machine Learning, Azure OpenAI, and common machine learning frameworks is an asset.Experience scaling and optimizing Databricks/Spark or Elasticsearch clusters is an asset.Experience with GPU-based infrastructure, vector databases, RAG architectures, or MLOps is an asset.Experience building internal developer platforms or working in platform engineering is an asset.Familiarity with Kubernetes and container orchestration concepts is beneficial.Experience with observability technologies such as Grafana, Prometheus, OpenTelemetry, New Relic, Datadog, or Rapid7 is a plus.Familiarity with additional Azure PaaS services, Jenkins, Octopus, Ansible, or similar automation tools is beneficial.Data-platform experience involving data pipelines, data lakes, Trino/Presto, Hadoop, or HDFS is an asset.Relevant Azure certifications, such as Azure DevOps Engineer Expert or Azure Solutions Architect Expert, are considered a plus. Benefits Remote work: Full-time remote position based in Canada.Technical ownership: Opportunity to shape DevOps, platform engineering, cloud infrastructure, and AI capabilities at scale.Leadership opportunity: Influence technical direction while mentoring engineers and driving cross-functional initiatives.Modern cloud environment: Hands-on work with Azure, Terraform, Docker, CI/CD, infrastructure automation, observability, and AI/data technologies.Professional growth: Exposure to advanced platform engineering, MLOps, DevSecOps, cloud architecture, and operational excellence.Collaborative environment: Work closely with Engineering, Security, NOC, and FinOps specialists.Continuous improvement: Culture focused on innovation, accountability, collaboration, and measurable operational improvements.Inclusive workplace: Commitment to diversity and an environment where colleagues are respected, supported, and encouraged to contribute different perspectives. How Jobgether Works We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether? Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.