About The Role We are a fast-growing semiconductor startup building next-generation silicon. Our design and verification pipelines rely on large-scale Linux compute infrastructure spanning AWS and on-prem environments.

We are seeking a senior, hands-on Cloud & Infrastructure IT Engineer to own the reliability, performance, and automation of our mission-critical EDA platforms. You will work directly with chip design teams to ensure our compute environments are fast, stable, secure, and ready to scale.

Requirements:

What You’ll Do

• Operate and scale hybrid AWS + on-prem Linux compute infrastructure for chip design and verification workloads.
• Own day-to-day reliability, performance tuning, capacity planning, and incident response.
• Build and maintain AWS environments using Terraform and Ansible.
• Automate provisioning of VPCs, IAM, EC2, FSx, EBS, S3, VPNs, and security controls.
• Tune Linux systems for CPU-, memory-, and I/O-intensive EDA workloads.
• Operate and optimize grid / job scheduling platforms such as Slurm, LSF, or Grid Engine.
• Design and manage high-throughput storage solutions for simulation pipelines.
• Develop automation and self-service tooling using Python and Bash.
• Implement observability and alerting using Prometheus and Grafana.
• Participate in on-call rotation and lead root-cause analysis for production incidents.

Required Qualifications

• AWS: VPC, EC2, IAM, FSx, EBS, S3, VPN, security controls
• Infrastructure as Code: Terraform, Ansible
• Linux / HPC: Kernel, filesystem, and network performance tuning
• Schedulers: Slurm / LSF / Grid Engine
• Automation: Python, Bash
• Observability: Prometheus, Grafana
• CI/CD: GitHub Actions / GitLab CI

Requirements

• 7+ years of hands-on experience operating large-scale Linux infrastructure.
• Strong experience managing AWS production environments.
• Advanced proficiency with Terraform, Ansible, Python, and Bash.
• Deep understanding of networking, storage, and Linux internals.
• Comfortable owning business-critical systems in a fast-moving startup.
• Experience supporting semiconductor / EDA / HPC workloads.

Preferred

• Exposure to Azure or GCP.
• Experience with cloud cost optimization / FinOps.