Introduction
At IBM Infrastructure & Technology, we design and operate the systems that keep the world running. From high-resiliency mainframes and hybrid cloud platforms to networking, automation, and site reliability. Our teams ensure the performance, security, and scalability that clients and industries depend on every day. Working in Infrastructure & Technology means tackling complex challenges with curiosity and collaboration. You'll work with diverse technologies and colleagues worldwide to deliver resilient, future-ready solutions that power innovation. With continuous learning, career growth, and a supportive culture, IBM provides the opportunities to build expertise and shape the infrastructure that drives progress.
Your Role And Responsibilities
As a Test Engineer specializing in Artificial Intelligence, you will drive the quality assurance and validation of next-generation AI solutions, contributing to cutting-edge initiatives involving machine learning, deep learning, and advanced automation technologies. In this role, you will play a key part in ensuring the reliability, scalability, and robustness of strategic offerings within IBM's AI infrastructure portfolio. Your primary responsibilities will include:
- Designing, developing, and maintaining scalable, reusable test frameworks adopted across multiple development teams.
- Integrating diverse test suites and validation workflows into DevSecOps-driven CI/CD pipelines for continuous quality assurance.
- Performing in-depth root cause analysis of pipeline and test execution failures to enable rapid troubleshooting and resolution.
- Collaborating with cross-functional development, QA, and platform engineering teams to understand testing requirements and continuously enhance shared automation frameworks.
- Leveraging AI-driven techniques for intelligent test selection, predictive validation, and optimized execution within the CI/CD lifecycle to improve efficiency and reduce pipeline runtime.
Required Technical And Professional Expertise
- 6–8 years of experience in software testing and quality engineering.
- Hands-on experience in day-to-day test execution, failure analysis, defect tracking, and defect lifecycle management.
- Strong Linux system administration and troubleshooting skills.
- Expertise in deploying, managing, and working with OpenShift Container Platform (OCP) clusters.
- Experience testing AI/ML frameworks such as PyTorch, TensorFlow, or similar technologies.
- Strong understanding of GPU/CUDA-based environments and AI infrastructure testing.
- Experience validating AI accelerators and their associated software ecosystems.
- Proven ability to design and develop reusable common test frameworks consumed across multiple teams.
- Experience in test optimization strategies, including selective and intelligent test execution.
- Good understanding of machine learning and deep learning concepts and workflows.
- Exposure to test automation methodologies and tools, including unit, integration, and functional testing.
- Experience collaborating with cross-functional teams to identify, troubleshoot, and resolve defects in AI solutions.
- Hands-on experience integrating and executing automated test suites within CI/CD pipelines.
- Ability to clearly communicate testing status, risks, and coverage gaps to stakeholders.
- Strong collaboration skills with development, CI/CD, platform engineering, and release management
Preferred Technical And Professional Experience
Preferred technical and professional experience
Proven knowledge on Deep learning, AI frameworks
Create Test frameworks & optimized test case execution
Python scripts, Bash, Groovy scripts in Jenkins pipeline
Experience in implementing AI for optimized test case selection & execution
Nice-to-Have
- Experience with Kubernetes and cloud-native AI platforms.
- Working knowledge of AI/ML frameworks, including: PyTorch
- IBM Z skills are added advantage
