76 to 100 of 666 Continuous Integration Jobs

cloud platforms (preferably GCP, with AWS or Azure as alternatives). You will be instrumental in managing our on-premises environments using Anthos, optimizing our infrastructure, and ensuring seamless integration and operation. Job Description: Design, implement, and maintain highly available, scalable, and secure infrastructure on Google Cloud Platform (GCP) using Anthos, Terraform, Kubernetes, ISTIO, and ArgoCD. Architect and manage … event-driven autoscaling using KEDA and Knative for efficient resource utilization and cost optimization. Streamline build and deployment processes using Maven, Gradle, Jenkins, and/or TeamCity to achieve continuous integration and continuous delivery (CI/CD). Set up robust tracing and observability tools, such as Stackdriver, Prometheus, Grafana, and Jaeger, to monitor system health, performance More ❯

for complex, real-time, mission-critical systems. Lead the software development process from architecture and design through to implementation and deployment, leveraging GitLab for version control, issue tracking, and continuous integration/continuous deployment (CI/CD). Oversees the design, development, analyses, and maintenance of software systems that meet design practices, customer and internal quality, safety … customer, operational and performance requirements and have clear traceability to design, code and test artifacts. Oversees completion of software system-level analyses to identify risk, issues and opportunities; oversees integration and deployment of mitigation actions throughout the software lifecycle. Oversees monitoring and reviewing test completion, verification processes and issue resolution for software systems. Oversees review of product and process More ❯

engineering environment. Proven experience managing QA teams, including training, performance management, and team development. In-depth knowledge of quality assurance methodologies, tools, and frameworks. All testing phases: Functional, Regression, Integration, System, UAT, and Usability in an Agile environment. In-depth knowledge of Agile, Scrum, and Waterfall methodologies and the ability to implement QA processes in an Agile environment. Background … Android development Experience with cloud-based QA tools and testing in a cloud environment (AWS, Azure) and AI testing tools. Familiarity with tools such as Jenkins or Git for continuous integration/continuous testing. Experience cross-browser and cross-device testing on iOS and Android platforms. Exposure to testing frameworks like Jasmine, Mocha, Karate. etc. Strong analytical More ❯

Job Overview: Key responsibilities include developing Application Programming Interfaces (APIs), implementing Continuous Integration and Continuous Delivery/Deployment (CI/CD) pipelines, optimising cloud performance, modernising applications to be cloud-ready, ensuring application security, and automating infrastructure using Infrastructure as Code (IaC). Experience in containerization (Docker, Kubernetes), serverless architecture, and cloud monitoring tools is preferred. Minimum More ❯

Cloud Automation Engineer/Cloud Infrastructure Engineer/Cloud Deployment Specialist/Cloud Operations Engineer/Cloud Platform Engineer/Cloud Solutions Engineer/Cloud Systems Engineer/Cloud Continuous Integration/Continuous Deployment (CI/CD) Engineer/Cloud DevOps Specialist/Cloud Automation Specialist/Graduate/Trainee/Junior ********************************************************************************* RedTech Recruitment Ltd focus on More ❯

to scaling a successful software engineering team in the region. The Role Working with Java and Spring Boot to design, implement and test scalable server-side microservices Contribute to Continuous Integration and Continuous Deployment (CI/CD) solutions with Jenkins Work with the product team and other engineering teams to gather requirements and focus on product integration More ❯

to scaling a successful software engineering team in the region. The Role Working with Java and Spring Boot to design, implement and test scalable server-side microservices Contribute to Continuous Integration and Continuous Deployment (CI/CD) solutions with Jenkins Work with the product team and other engineering teams to gather requirements and focus on product integration More ❯

to scaling a successful software engineering team in the region. The Role Working with Java and Spring Boot to design, implement and test scalable server-side microservices Contribute to Continuous Integration and Continuous Deployment (CI/CD) solutions with Jenkins Work with the product team and other engineering teams to gather requirements and focus on product integration More ❯

closely with the engineering leadership to ensure quality is built in early and is testable Develop and participate in the QA/test approach, methodology, and process for a Continuous Integration/Continuous Delivery (CI/CD) environment Test applications through automated and manual back-end functions as well as through UI Qualify all new features by More ❯

perfectly. - Develop automated test scripts using tools like Selenium, and write code in Python, JavaScript, and Bash. - Work with tools like Jenkins to automate testing as part of our continuous integration/continuous deployment (CI/CD) process. - Collaborate with our engineers and data scientists to spot and fix bugs. - Use AWS for setting up testing environments More ❯

to obtain a TS/SCI US Security Clearance (Post-Start) 3+ years of experience leading projects and/or individuals in software development lifecycle tasks Experience working in Continuous Integration and Continuous Development (CI/CD) using appropriate code versioning, build and test automation tools Experience/proficiency with Java Preferred Qualifications (Desired Skills/Experience More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯

in production. Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models. Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code. Ensure all code is well-managed More ❯