Responsibilities
- Collaborate with full stack engineers to design, implement, and maintain automated testing frameworks for both frontend and backend systems.
- Participate in the development and execution of test plans and test cases to verify the functionality, usability, and performance of our software applications.
- Set up and maintain the continuous integration/continuous deployment (CI/CD) pipelines to automate the build, test, and deployment processes for application and infrastructure.
- Evaluate and integrate AI-powered DevOps tools to enhance pipeline intelligence, including automated anomaly detection, predictive incident response, and AI-assisted code review or test generation within Azure DevOps workflows.
- Work with cross-functional teams to identify areas for process improvement and implement best practices for software development, testing, and deployment.
- Monitor systems, identify performance bottlenecks, and implement solutions proactively.
- Ensure critical resolution of system issues by using the best cloud secured solutions.
- Develop and maintain design and troubleshooting documentation.
- Run agile scrum meetings when needed.
- Stay up to date with emerging technologies, tools, and trends in DevOps and Quality Assurance to drive innovation and efficiency within the organization.
- Proven subscription to the company’s core values of integrity, trust and respect, innovation, stewardship, excellence, and celebration.
- Plan disaster recovery measures and maintain data storage security in Azure.
Qualifications
- Bachelor’s degree in computer science, engineering, or a related field required (recent graduates and candidates nearing completion encouraged to apply), with 1–3 years of relevant experience. Candidates holding an associate’s degree must have a minimum of 5 years of experience.
- Proven experience in Azure DevOps, cloud computing, and DevOps methodologies.
- Strong understanding of Azure services, CI/CD pipelines, and automation tools.
- Experience with software development methodologies such as Agile or Scrum.
- Experience with programming/scripting languages such as Python, C#, Java, or JavaScript.
- Experience with administration of version control systems (e.g., Git) and issue tracking systems (e.g., Jira).
- Familiarity with monitoring and logging tools like Azure Monitor, Log Analytics, and Application Insights.
- Familiarity with SonarQube, Snyk or Veracode; Equivalent Code Quality tools integration into CICD and IDE
- Familiarity with AI SDLC process working with Claude or OpenAI or Copilot code assist or agentic tools
- Familiarity about the SAST, DAST and other code review tools
- Understanding network configurations and security best practices in Azure.
- Familiarity with AI/ML operationalization (MLOps) concepts and experience supporting the deployment or monitoring of AI models in cloud environments, such as Azure Machine Learning, is a plus.
- Experience with automated testing frameworks and tools.
- Knowledge of database management systems and data storage solutions in Azure.
- Strong analytical and problem-solving skills with attention to detail.
- Excellent communication and teamwork abilities.
- Prior experience with DevOps tools (e.g., Jenkins, Docker, Kubernetes) and QA automation frameworks (e.g., Selenium) is a plus.