Company:
Han IT Staffing
Location: Iselin
Closing Date: 28/11/2024
Hours: Full Time
Type: Permanent
Job Requirements / Description
We are seeking a highly skilled and motivated Quality Engineer with expertise in AWS, artificial intelligence (AI), resiliency, and performance testing. The ideal candidate will possess a strong background in quality assurance, a passion for cutting-edge technology, and the ability to ensure our systems are robust, resilient, and perform optimally under all conditions. This role will require close collaboration with development, operations, and product teams to deliver high-quality solutions that meet our business objectives.
Key Responsibilities
Quality Assurance and Testing
Develop and execute comprehensive test plans, test cases, and test scripts for AWS-based applications and AI-driven solutions.
Ensure all functional, integration, system, and regression testing is completed thoroughly and efficiently.
Implement automated testing frameworks and tools to improve testing efficiency and coverage.
Collaborate with developers to identify, reproduce, and resolve defects.
Performance Testing
Design and implement performance testing strategies to validate the scalability, reliability, and performance of our applications.
Use performance testing tools (e.g., JMeter, LoadRunner, Gatling) to simulate user load and identify performance bottlenecks.
Analyze performance test results and provide detailed feedback and recommendations for improvement.
Work with development and operations teams to optimize application performance and ensure it meets our standards and SLAs.
Resiliency Testing
Develop and execute resiliency testing plans to ensure our applications can withstand and recover from unexpected failures and disruptions.
Implement chaos engineering principles and tools (e.g., Chaos Monkey, Gremlin) to test the robustness of our systems.
Collaborate with development and operations teams to identify vulnerabilities and implement strategies to improve system resiliency.
Artificial Intelligence
Develop and execute testing strategies for AI and machine learning models to ensure their accuracy, reliability, and robustness.
Collaborate with data scientists and AI engineers to validate model performance and ensure they meet business requirements.
Implement monitoring and validation techniques to ensure AI models continue to perform well in production environments.
Continuous Improvement
Continuously evaluate and improve our testing processes, tools, and methodologies to ensure high standards of quality and efficiency.
Stay updated with industry trends, best practices, and emerging technologies in quality engineering, AI, and cloud computing.
Provide mentorship and guidance to junior quality engineers and contribute to the overall growth and development of the QA team.
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field.
At least 5 years of experience in quality assurance and performance testing.
Strong expertise in AWS services and cloud-based applications.
Experience with AI and machine learning testing.
Proficiency in automated testing tools and frameworks (e.g., Selenium, JUnit, TestNG).
Experience with performance testing tools (e.g., JMeter, LoadRunner, Gatling).
Understanding of chaos engineering principles and tools (e.g., Chaos Monkey, Gremlin).
Excellent analytical, problem-solving, and communication skills.
Ability to work collaboratively in a fast-paced, agile environment.
Strong attention to detail and commitment to quality.
Preferred Skills
Advanced certifications in AWS and related technologies.
Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch).
Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).
Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
Key Responsibilities
Quality Assurance and Testing
Develop and execute comprehensive test plans, test cases, and test scripts for AWS-based applications and AI-driven solutions.
Ensure all functional, integration, system, and regression testing is completed thoroughly and efficiently.
Implement automated testing frameworks and tools to improve testing efficiency and coverage.
Collaborate with developers to identify, reproduce, and resolve defects.
Performance Testing
Design and implement performance testing strategies to validate the scalability, reliability, and performance of our applications.
Use performance testing tools (e.g., JMeter, LoadRunner, Gatling) to simulate user load and identify performance bottlenecks.
Analyze performance test results and provide detailed feedback and recommendations for improvement.
Work with development and operations teams to optimize application performance and ensure it meets our standards and SLAs.
Resiliency Testing
Develop and execute resiliency testing plans to ensure our applications can withstand and recover from unexpected failures and disruptions.
Implement chaos engineering principles and tools (e.g., Chaos Monkey, Gremlin) to test the robustness of our systems.
Collaborate with development and operations teams to identify vulnerabilities and implement strategies to improve system resiliency.
Artificial Intelligence
Develop and execute testing strategies for AI and machine learning models to ensure their accuracy, reliability, and robustness.
Collaborate with data scientists and AI engineers to validate model performance and ensure they meet business requirements.
Implement monitoring and validation techniques to ensure AI models continue to perform well in production environments.
Continuous Improvement
Continuously evaluate and improve our testing processes, tools, and methodologies to ensure high standards of quality and efficiency.
Stay updated with industry trends, best practices, and emerging technologies in quality engineering, AI, and cloud computing.
Provide mentorship and guidance to junior quality engineers and contribute to the overall growth and development of the QA team.
Qualifications
Bachelor's degree in Computer Science, Engineering, or a related field.
At least 5 years of experience in quality assurance and performance testing.
Strong expertise in AWS services and cloud-based applications.
Experience with AI and machine learning testing.
Proficiency in automated testing tools and frameworks (e.g., Selenium, JUnit, TestNG).
Experience with performance testing tools (e.g., JMeter, LoadRunner, Gatling).
Understanding of chaos engineering principles and tools (e.g., Chaos Monkey, Gremlin).
Excellent analytical, problem-solving, and communication skills.
Ability to work collaboratively in a fast-paced, agile environment.
Strong attention to detail and commitment to quality.
Preferred Skills
Advanced certifications in AWS and related technologies.
Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch).
Knowledge of containerization and orchestration tools (e.g., Docker, Kubernetes).
Familiarity with CI/CD pipelines and tools (e.g., Jenkins, GitLab CI).
Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack).
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