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
