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Deepomatic

DevOps Engineer

Posted Updated
Discussion
  • IQGeo is seeking a DevOps Engineer to play an integral role in supporting our global Engineering teams from our Cambridge, UK office. This role joins a dynamic team focused on building and maintaining tools and automation to streamline the software development lifecycle, reduce cognitive load for engineering teams, and improve release velocity
  • Design, develop, and maintain CI/CD pipelines to automate software builds, testing, and releases
  • Build and maintain internal tooling to support the software development lifecycle (e.g., code quality analysis, dependency management, automated testing)
  • Collaborate with engineering teams to identify and automate manual processes, reducing cognitive load and improving efficiency
  • Implement and maintain infrastructure as code (IaC) for internal development environments
  • Work closely with development teams to troubleshoot and resolve issues related to build processes, testing, and deployments
  • Coordinate penetration testing, code/virus scanning, and disseminate findings to the engineering team for resolution
  • Measure performance and environment of applications with system and application log tools
  • Work with Product Engineering to ensure technical alignment and best practice approaches are used
  • Evaluate and implement new tools and technologies to improve developer experience and release velocity
  • Use AI coding assistants to accelerate authoring of CI/CD pipeline configurations, IaC scripts, and automation tooling
  • Apply AI-assisted security scanning (SAST) as an automated merge gate across engineering pipelines
  • Support delivery teams and partners to reduce the complexity of implementing IQGeo solutions
  • Participate in an on-call rotation

Benefits

  • Flexible schedules
  • Collaborative teams
  • New and modern office facilities
  • Remote work opportunities
  • Ability to critically evaluate AI-generated outputs for correctness, security, performance and maintainability
  • Ability to translate business requirements into structured specifications prior to implementation (Spec-Driven Development)
  • Experience using AI to generate and maintain automated unit, API and integration tests
  • Proficient in AI-assisted software development using modern coding assistants to accelerate design, implementation, testing and documentation
  • Strong prompt engineering skills for software engineering tasks including code generation, test generation, debugging, documentation and architecture
  • Demonstrated ability to work with AI agents while retaining full engineering ownership and accountability
  • Candidates must demonstrate the ability to work effectively in an AI-First Software Development Lifecycle
  • Experience with containerisation and orchestration technologies including Docker and Kubernetes
  • Experience with bug tracking tools and code repositories
  • Experience with CI/CD tools (e.g., Jenkins, GitHub Actions)
  • Strong knowledge of Linux operating systems
  • Experience using Git or other distributed version control systems
  • Excellent organisational skills and attention to detail
  • Fluent written and spoken English
  • Proficient scripting skills (Python, BASH, JavaScript)
  • Experience with cloud platforms (AWS, Azure, GCP)
  • Proven ability to work independently and collaboratively in a distributed remote team environment
  • Experience with infrastructure as code tools (e.g., Terraform)
  • Excellent analytical and problem-solving skills
  • Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack)
  • Experience with configuration management tools (e.g., Ansible, Puppet, Chef)
  • Experience with code quality analysis tools (e.g., SonarQube, Snyk)
  • Experience with dependency management tools (e.g., Maven, Gradle, npm, pip)
  • Experience with automated testing frameworks
  • Experience with Node.js design and development
  • Experience working in an Agile software engineering environment

Skills

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See also

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