THE ROLE:
Ideal candidate should have 7 to 12 years of experience in technical roles involving tool development with some focus in areas of regression management like scheduling, executing harness, failure analysis & assignment and reporting. Also should have hands-on experience in working with DevOps env tools including cloud, databases & AI/ML technologies.
THE PERSON:
- The ideal candidate should be passionate about software engineering and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD.
KEY RESPONSIBILITIES:
- Drive and improve implementation of test infrastructure to provide robust test environment to developers & testers
- Analyze, optimize & improve current architecture of various components of test Infra tools including integration
- Implement containerized test infra with full on-prem/cloud portability Compatible with various job management systems like LSF, SLURM, and Kubernetes orchestration framework
- Drive & Implement strategies to leverage AI/ML models at various stages of testinfra
- Drive & Implement Next Gen QOR (Quality of results for FPGA designs) regression execution & reporting
- Overseeing and providing development support to team members.
- Collaborating with cross-functional teams, providing technical support, and troubleshooting migration to next generation tools, CI/CD, containerization, Kubernetes, and cloud tooling issues.
- Creating comprehensive documentation, mentoring junior team members, and conducting training sessions
PREFERRED EXPERIENCE:
- Professional 8+ yrs of technical experience and at least 5 years experience in design & implementation of product developments
- Strong knowledge in CI/CD tools and DevOps practices.
- Experience in developing tools around test Infra automation
- Expert in structured & OOP in Python
- Proficiency in Scripting and automation languages (e.g., Python, Bash, Csh,..)
- Linux & Windows shells working environment
- Understanding of AI/ML principles and some experience in applying LLM & ML models in tool development
- Experience with working in DevOps environment like GitHub, Perforce version control systems, containerization technologies like Docker, Kubernetes orchestration and CI/CD pipelines using Jenkins or Github actions
- Additionally, experience with monitoring and logging tools for containerized environments (e.g., Prometheus, Grafana)
- Excellent problem-solving abilities with a keen eye for detail are highly valued
ACADEMIC CREDENTIALS:
- Bachelor s or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
