Gauss Labs is a leading innovator in AI solutions for the semiconductor industry. Our mission is to accelerate innovation by building cutting-edge, intelligent solutions that push the boundaries of what’s possible in manufacturing and beyond.
We are seeking a passionate and experienced DevOps Engineer to join our dynamic team. You will play a critical role in building and maintaining scalable infrastructure, managing CI/CD pipelines, and deploying cloud-native and bare-metal applications. This role requires a high level of technical expertise, a collaborative mindset, and a strong desire to continuously improve systems and processes

BASIC QUALIFICATIONS

• 5-10 years of DevOps or Software engineering experience.
• Proficiency with cloud platforms (AWS preferred).
• Hands-on experience with Kubernetes and containerized applications.
• Strong experience with CI/CD tools like GitHub Actions, ArgoCD, or similar.
• Experience managing infrastructure using Terraform, or other IaC tooling.
• Ability to read and debug code in at least one programming language (Python, Go, etc).
• Familiarity with monitoring/observability tools (Prometheus, Grafana, ELK, etc.).
• Scripting and automation skills (Python, Bash, etc.).
• Strong understanding of networking, security, and distributed systems.

PREFERRED QUALIFICATIONS

• Proven ability to work closely with developers and understand application behavior and system interactions.
• Experience with hybrid deployment environments or the semiconductor/manufacturing domain.

• Design, implement, and manage CI/CD pipelines for multiple applications and services.
• Build and maintain infrastructure-as-code (IaC) using tools like Terraform.
• Manage Kubernetes (EKS) clusters, container orchestration, and application deployment strategies.
• Troubleshoot complex issues across systems, infrastructure, and application layers—including diving into application code, logs, and metrics to assist in root cause analysis.
• Support hybrid deployment models, including both cloud-native and on-premise environments.
• Automate operational workflows and ensure system reliability, scalability, and security.
• Collaborate with engineering teams to understand requirements and provide infrastructure support.
• Monitor systems and implement observability best practices.
• Participate in on-call rotations and incident response.