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Checked on their board 13 Nov

Gauss Labs Hiring now

Forward-Deployed Site Reliability Engineer (KR)

AI for chip factories that runs at customer sites. You'd own on call and monitoring for the platform layer.

Seoul, South KoreaHybridFull-timePosted 4 months ago
Who to email about itThe Head of Engineering at Gauss Labs
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About the role

From Gauss Labs's posting on Lever, as they wrote it

Gauss Labs is an industrial AI company on a mission to revolutionize manufacturing with AI, starting with the semiconductor sector. Panoptes is an AI-based process intelligence solution deployed in high-volume manufacturing fabs, helping customers improve yield, reduce costs, and accelerate production. Our software runs in our customers’ own managed environments. As our Site Reliability Engineer, you are the first responder for the platform layer that Panoptes runs on in production at the customer site, and you own its on-call rotation. You won’t control the cluster/node layer; your job is to diagnose what the platform needs, make the case to the customer’s infrastructure team, and keep the platform reliable within their constraints. You will also own monitoring and alerting for the platform layer, and build the automation and observability that reduce operational toil and speed up incident response.

Responsibilities

  • Incident Response and On-call: Own first-response and the on-call rotation for the platform layer. Alerts are routed to the owning team and when an internal incident spans more than one team, this role coordinates the response in the incident channel.
  • Customer-environment operations and technical communication: Deploy and operate Panoptes at the application-namespace level in the customer-managed environment. The cluster, node, and Kubernetes layer is controlled by the customer’s infrastructure team: diagnose what the platform needs, make the technical case to that team, and operate within their setup, decisions, and constraints.
  • Internal cloud (AWS) environment: Own the platform layer end-to-end in our internal development environment — cluster health, resource management (CPU/memory/OOM), scheduling, autoscaling, and Kubernetes/EKS lifecycle.
  • Monitoring and Alerting: Build and maintain robust monitoring and alerting for the infrastructure and platform layer to proactively identify and resolve issues before they impact the platform.
  • Automation: Develop automation tools and scripts to streamline operations, reduce manual effort, and enable engineering teams to operate their own services safely.
  • Capacity Planning: Forecast resource needs, optimize resource utilization, and ensure the platform infrastructure can handle increasing workloads.
  • Deployment infrastructure: Build and maintain CI/CD pipelines and deployment infrastructure for the platform.
  • Continuous Improvement: Drive a culture of continuous improvement by identifying opportunities to enhance platform reliability, performance, and efficiency.

Basic Qualifications

  • Bachelor's degree in computer science, engineering, or a related discipline
  • 5+ years of industry experience as a Site Reliability Engineer or in platform/infrastructure engineering
  • Experience operating workloads on a cluster controlled by another team, and communicating technical needs across that boundary
  • Hands-on experience operating Kubernetes in production (EKS preferred): cluster lifecycle, scheduling, autoscaling, resource management
  • Experience with cloud platforms (AWS preferred) and containerization technologies (Docker, Kubernetes)
  • Experience with observability and alerting tools (Prometheus, Grafana, ElasticSearch, Jaeger)
  • Experience with scripting languages (Python, Bash)
  • Working knowledge of GitHub, GitHub Actions, and CI/CD concepts
  • Strong problem-solving and troubleshooting skills
  • Working proficiency in English for internal documentation and technical coordination

Preferred Qualifications

  • Knowledge of AI/ML infrastructure and workloads.
  • Knowledge of database technologies (MongoDB, PostgreSQL)
  • Experience operating systems in an environment you didn’t fully control — a customer site, on-prem, an MSP, or another team’s cluster
  • Experience leading incidents from diagnosis through root cause
  • Exposure to manufacturing, semiconductor, or enterprise B2B customer environments

[Interview process]

Application reivew - Phone interview - Virtual onsite interview - VP interview/Core Value interview - CEO interview

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About Gauss Labs

Gauss Labs is an industrial AI company on a mission to revolutionize manufacturing with AI, starting with the semiconductor sector.

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