Infrastructure and DevOps Engineer
Job Description
Job Description
Intel Performance Libraries Infrastructure team is looking for an experienced Infrastructure and DevOps engineer. IPL Infra is dedicated to providing reliable infrastructure to support the product development process and boost the productivity of developer teams. Our strategic goals include facilitating business processes for development teams, ensuring smooth product releases, adhering to corporate and business unit standards, maintaining stable infrastructure, and enabling scalable and manageable value-added solutions. As part of this role, you will design and deploy automation solutions for continuous testing of several performance libraries. In this role you will be responsible for efficiently managing the setup, maintenance, and operation of both hardware and software systems needed for developing and releasing various projects and products. Collaborates closely with development and quality teams to understand infrastructure needs, develop and test appropriate tools, and ensure compliance with Intel's IT guidelines and other regulatory bodies. Oversees the entire delivery process, from managing source code to release staging and disaster recovery planning. Proactively identifies areas for automation and improvement in pipeline efficiency and reliability by implementing monitoring systems and industry best practices, especially AI-based enhancements.Qualifications
Minimum qualifications:
- BSc or MSc in Computer Science with 2+ years of relevant DevOps experience
- Hands-on experience/proficiency in the following areas:
CI/CD pipelines with Infrastructure as Code (IaC) concept.
One or more build management tools e.g. Jenkins, GitHub Actions
One or more scripting languages e.g. Bash, PowerShell
Good knowledge of Python is mandatory
Advanced knowledge of Linux and/or Windows administration
- Strong interpersonal, communication, and results-oriented skills
- Great critical thinking and problem-solving skills
- Effectively communicate in English
Nice to have:
Some exposure to AI and knowledge of MLOps.
Experience with public/private cloud computing platforms (e.g. AWS, GCP, Azure, OpenStack)
Containerization (e.g. Docker) and orchestration (Kubernetes)
Configuration/Infrastructure automation management with one or more of the following: Ansible, Salt Stack, Chef, Puppet etc.
Monitoring and observability tools e.g. Prometheus, Grafana, New Relic, Zabbix