Kubernetes Platform Engineer for AI Workloads & Scale

Bluetab, An Ibm Company

Tarragona

Híbrido

EUR 70.000 - 110.000

Jornada completa

Hace 3 días
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Descripción de la vacante

Synopsys is building a SimAI platform to accelerate simulation and AI-driven engineering. You will join a team designing, deploying, and scaling the platform infrastructure with Kubernetes, Pulumi, Terraform, and related tools.

The role emphasizes production-grade reliability, scaling resources for AI workloads, and mentoring engineers across RFCs and documentation. Ideal candidates have deep distributed-systems experience, strong troubleshooting, and a passion for end-to-end ownership in a

Formación

  • Software development certification with 3+ years in complex platforms.
  • Advanced troubleshooting skills.
  • Distributed systems design and operation experience (Kubernetes, Pulumi, NATS, Redis).
  • Proficiency in Bash scripting and programming in Python or TypeScript.
  • Ability to own problems end to end and work independently.

Responsabilidades

  • Perform complex development activities including cloud deployment and distributed system scaling.
  • Use best practices and evangelize through RFCs and mentoring.
  • Help scale processes (release, development environments, CI/CD pipelines).
  • Root cause investigation, automated release testing, production incident solving.
  • Design, deploy, and maintain platform infrastructure using Kubernetes, Pulumi, and Terraform.
  • Scale GPU/CPU compute to support AI training/inference workloads.

Conocimientos

Advanced troubleshooting
Distributed systems experience
Independent work
End-to-end ownership
Problem solving

Herramientas

Kubernetes
Pulumi
NATS
Redis
Bash
Python
TypeScript

Descripción del empleo

Synopsys is building a SimAI platform to accelerate simulation and AI-driven engineering. You will join a team designing, deploying, and scaling the platform infrastructure with Kubernetes, Pulumi, Terraform, and related tools.

The role emphasizes production-grade reliability, scaling resources for AI workloads, and mentoring engineers across RFCs and documentation. Ideal candidates have deep distributed-systems experience, strong troubleshooting, and a passion for end-to-end ownership in a

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