Systems Engineer-AI

As a member of Zenlayer

You are ACTION ORIENTED – able to understand technical priorities, manage multiple tasks and deliver solutions within deadlines. You are a TEAM PLAYER with a strong sense of ownership, responsibility and a proactive attitude. You are also analytical, detail-oriented and passionate about exploring new technologies, particularly Artificial Intelligence (AI) and cloud infrastructure.

At Zenlayer, we value teamwork, innovation, efficiency and customer service excellence. As part of our engineering team, you will have the opportunity to work with cutting-edge technologies, contribute to AI-driven initiatives and support the development and optimization of our global infrastructure.

About the Role

As a Systems Engineer – AI, you will be responsible for supporting, designing, implementing and maintaining system infrastructure, with a particular focus on AI-related technologies and solutions.

You will work closely with the engineering, infrastructure and development teams to deploy and optimize AI workloads, manage system environments, and explore the integration of AI technologies into existing systems and business operations.

The ideal candidate should have a solid foundation in system administration, Linux environments, cloud infrastructure and automation, together with a strong interest or hands-on experience in AI, Machine Learning and Large Language Models (LLMs).

Responsibilities

System Engineering & Infrastructure Management

• Design, deploy, configure and maintain Linux-based systems and server infrastructure.

• Monitor system performance, availability and reliability, and troubleshoot infrastructure-related issues.

• Support server provisioning, system upgrades, patch management and infrastructure optimization.

• Manage virtualization, containerization and related infrastructure environments.

• Work with network and infrastructure teams to ensure system connectivity, stability and security.

• Maintain technical documentation, system configurations and operational procedures.

AI Infrastructure & Integration

• Support the deployment, configuration and maintenance of AI-related infrastructure and applications.

• Assist in setting up and managing GPU-based computing environments for AI and Machine Learning workloads.

• Work with AI technologies, including Large Language Models (LLMs), Generative AI and Machine Learning frameworks.

• Support AI model deployment, testing, monitoring and performance optimization.

• Explore and implement AI-powered tools and solutions to improve system operations and automation.

• Integrate AI services, APIs and automation tools into existing systems and workflows.

• Stay updated on emerging AI technologies and identify opportunities to apply them to infrastructure and business operations.

Automation & Technical Support

• Develop and maintain automation scripts using Python, Bash or other scripting languages.

• Automate routine system administration, monitoring and maintenance tasks.

• Support DevOps practices, CI/CD pipelines and infrastructure automation.

• Investigate technical incidents, identify root causes and implement effective solutions.

• Collaborate with cross-functional engineering teams on infrastructure and AI-related projects.

• Handle other technical projects and ad-hoc engineering tasks as assigned.

Candidate’s Skills & Qualifications

• Diploma or Bachelor's Degree in Computer Science, Information Technology, Computer Engineering or a related discipline.

• At least 5 years of experience in Systems Engineering, Infrastructure Engineering, System Administration or a related technical role.

• Strong knowledge of Linux system administration and server management.

• Familiarity with cloud computing platforms such as AWS, Microsoft Azure or Google Cloud.

• Experience with scripting languages such as Python, Bash or Shell scripting.

• Understanding of networking fundamentals, TCP/IP, DNS, routing and troubleshooting.

• Familiarity with Docker, Kubernetes or other containerization technologies.

• Basic understanding of AI, Machine Learning, Generative AI and Large Language Models (LLMs).

• Strong troubleshooting, analytical and problem-solving skills.

• Ability to work independently and collaboratively in a fast-paced environment.

• Strong sense of ownership, responsibility and willingness to learn new technologies.

• Good command of written and spoken English.

Preferred Qualifications

• Hands-on experience with AI infrastructure, GPU computing or AI model deployment.

• Experience working with NVIDIA GPUs, CUDA or GPU resource management.

• Familiarity with AI/ML frameworks such as PyTorch or TensorFlow.

• Experience with LLM integration, RAG (Retrieval-Augmented Generation), LangChain or AI APIs.

• Knowledge of MLOps, model serving and AI workload optimization.

• Experience with Kubernetes-based infrastructure and cloud-native technologies.

• Relevant certifications in AWS, Azure, Kubernetes, Linux or AI/ML technologies.

• Previous experience in cloud computing, data centers, telecommunications or technology infrastructure environments.