Infrastructure Operations Engineer (GPU Computing) - Enterprise AI

Aethir is a pioneering technology company at the forefront of GPU-based compute infrastructure, specializing in cutting-edge solutions for diverse industries ranging from AI and machine learning to high-performance computing (HPC). We're dedicated to pushing the boundaries of what's possible, leveraging the latest advancements in hardware and software to empower our clients with unparalleled computational capabilities.

About the Role:

We are seeking a highly skilled and motivated Infrastructure Operations Engineer to join our dynamic team. As an integral member of the InfraOps team, you will play a key role in managing and optimizing our GPU-based compute infrastructure (across multiple locations and partners), ensuring maximum performance, scalability, and reliability.

Responsibilities:

• Infrastructure Management: Deploy, configure, and maintain GPU-based compute infrastructure, including servers, storage, networking, and associated software stack. Aethir facilitates compute from dozens of providers around the world, from 4090s to H200s.
• Monitoring and Optimization: Implement robust monitoring and alerting systems to proactively identify performance bottlenecks, resource constraints, and potential failures. Continuously optimize infrastructure to improve performance, efficiency, and cost-effectiveness.
• Automation and Orchestration: Develop automation scripts and tools to streamline deployment, configuration, and management of infrastructure components. Implement infrastructure as code (IaC) principles to enable rapid provisioning and scaling.
• Security and Compliance: Implement and enforce security best practices to safeguard sensitive data and ensure compliance with relevant regulations and industry standards. Conduct regular security audits and vulnerability assessments.
• Incident Response and Troubleshooting: Provide tier-3 support for infrastructure-related issues, investigating root causes and implementing timely resolutions. Participate in on-call rotation to respond to critical incidents outside of regular business hours.
• Capacity Planning and Scaling: Collaborate with cross-functional teams to forecast resource requirements, plan capacity upgrades, and scale infrastructure to accommodate growing workloads and user demands.
• Documentation and Knowledge Sharing: Maintain comprehensive documentation of infrastructure configurations, procedures, and troubleshooting guidelines. Share knowledge and best practices with team members to foster continuous learning and skill development.

• Experience in infrastructure operations, preferably in a DevOps or SRE role or Sales Engineering or Solution Architect role - focused on GPU compute.
• Proficiency in managing GPU-based compute infrastructure, including NVIDIA GPUs and CUDA programming.
• Strong expertise in Linux system administration and shell scripting (e.g., Bash, Python).
• Experience with configuration management tools (e.g., Ansible, Chef, Puppet) and version control systems (e.g., Git).
• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Solid understanding of networking concepts, protocols, and troubleshooting techniques.
• Excellent analytical and problem-solving skills, with a proactive and results-oriented mindset.
• Effective communication skills and the ability to collaborate effectively with cross-functional teams. We operate in English, but speaking Mandarin as well is a big bonus as we have engineering teams in China and Southeast Asia.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and hybrid cloud architectures.
• Knowledge of HPC frameworks and job scheduling systems (e.g., Slurm, PBS Pro).
• Familiarity with GPU-accelerated libraries and frameworks (e.g., TensorFlow, PyTorch, CUDA Toolkit).
• Understanding of cybersecurity principles and practices, including encryption, access controls, and threat detection/prevention.
• Bonus if you know Web3 (cryptocurrency, tokenization of RWAs, mining/staking, etc.).

• Competitive compensation structure (and flexible on fiat/token mix).
• Can be flexible on benefits, depending on location and setup.
• Salary is also flexible depending on location and setup.
• Flexible work hours and remote work options.