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Thomson Reuters

Legal, financial data, and media services

Staff Devops Engineer

Platform EngineeringUpdated on Nov 9
Full-timeNo salary listed

About the Job

Requirements

  • Strong hands-on experience with Microsoft Azure and AWS.
  • Deep experience with cloud-native architecture, distributed systems, serverless services, storage, virtual machines, managed application platforms, messaging, APIs, and relational and NoSQL databases.
  • Strong hands-on experience with Kubernetes and AKS, including application modernization and GPU workload deployment.
  • Hands-on experience with Helm for Kubernetes package management.
  • Skill in Infrastructure as Code with Terraform and Bicep.
  • Strong CI/CD experience with GitHub Workflows, GitHub Actions, and Argo CD.
  • Experience deploying and supporting .NET applications.
  • Good working knowledge of Linux.
  • Skill in shell scripting and Python.
  • Experience with Datadog, Azure Application Insights, or similar monitoring and observability tools.
  • A track record of finding and delivering cloud cost savings.
  • Working knowledge of Azure AI Foundry.
  • Experience building shared platform engineering capabilities used by multiple product teams.
  • Experience putting enterprise-scale GitOps and cloud governance practices in place.
  • Experience supporting AI/ML platforms, generative AI solutions, or GPU-enabled infrastructure.
  • Experience working in a complex enterprise or regulated software environment.

Responsibilities

  • Design, build, and run secure, scalable, highly available cloud-native platforms on Microsoft Azure and AWS, using the stated Azure and AWS services.
  • Lead the move of legacy and .NET applications to cloud-native, containerized architectures.
  • Own Kubernetes and AKS architecture, deployment, security, scalability, resiliency, and day-to-day operations, including GPU-based AI and machine learning workloads.
  • Use Helm to standardize application packaging and deployment, and create reusable platform patterns across applications, teams, and environments.
  • Build and maintain secure, compliant, version-controlled Infrastructure as Code with Terraform and Bicep; create reusable infrastructure modules and deployment patterns.
  • Expand automation and self-service so developers can deliver faster and more consistently.
  • Design, build, and improve CI/CD pipelines with GitHub Workflows, GitHub Actions, and Argo CD; advance GitOps practices and automated deployment strategies across environments.
  • Design and troubleshoot cloud networking, including VNets, subnets, network interfaces, private endpoints, DNS, load balancing, and network security.
  • Set up monitoring and observability with Datadog, Azure Application Insights, and related tools; define alerts, health indicators, and incident response practices.
  • Lead root cause analysis to prevent recurring incidents.
  • Find and lead cloud cost optimization work across Azure and AWS; balance cost, performance, security, reliability, and scalability in architecture decisions.
  • Promote practical governance, resource usage standards, and engineering ownership of cloud spend.
  • Advise on cloud, DevOps, and platform engineering; mentor engineers and raise standards for architecture, automation, quality, and delivery.
  • Lead the creation of reference architectures, technical standards, and best practices; shape platform strategy and explain decisions, risks, and trade-offs to technical and non-technical stakeholders.

Desired Qualifications

  • Relevant Azure, AWS, Kubernetes, or Terraform certifications.

About the Company

Thomson Reuters

Legal, financial data, and media services

Thomson Reuters provides intelligent information and professional services for law, tax, finance, and media. It serves law firms, corporations, government agencies, and financial institutions with platforms like legal research (Westlaw), tax software (UltraTax CS), financial market data, and news services. These products are accessed through subscription-based platforms, ensuring ongoing updates and a steady revenue stream. The company also monetizes through advertising on media platforms and data analytics sales. It distinguishes itself by offering a broad, integrated suite of industry-specific tools combined with AI, cognitive computing, and machine learning to improve accuracy, efficiency, and predictive analytics in research and data insights. Its goal is to be a trusted partner that helps professionals make informed decisions by delivering reliable information and decision-ready tools while pursuing responsible, values-driven initiatives.

Company size
10,001+
Company stage
IPO
Headquarters
Toronto, Canada
Founded
1851

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