DevOps Platform Engineer

Amd

Confirmed live today High trust

Quick summary

Work type
On-site
Location
San Jose, CA
Salary
$136,000–$204,000 / yr
Posted
22 days ago
Freshness
Confirmed live today
Closes
Sep 9, 2027

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $156k
This role $170k
$92k most similar roles pay here $219k

This role pays more than 69% of similar roles. Most pay $126,800–$185,675 — the shaded band above. At the midpoint, this role pays about $170k versus about $156k for comparable roles.

Based on 240 similar postings.

Employer

About Amd

AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors

Amd currently has 474 open roles on FindRole.

Listed pay typically runs $166,400–$249,600 across 474 roles with salary data.

Most-posted roles

View all roles at Amd

At a glance

TL;DR · DevOps Platform Engineer

The Devops Platform Engineer joins the team to build and operate infrastructure foundations that enable engineering teams to deliver reliable, scalable, and secure products. This role focuses on shaping the internal developer platform across Kubernetes, observability, CI/CD, and infrastructure as code. You will design and manage scalable Kubernetes-based capabilities for development and production workloads while creating reusable modules using Terraform, Ansible, Helm, or Kustomize. The position involves developing platform observability through metrics, logs, and traces, and building the necessary infrastructure to deploy and govern AI/ML workloads involving GPU-enabled compute and model serving. Key technical requirements include proficiency in Python, Go, Bash, or TypeScript, along with experience in GitOps, service mesh, and container technologies like Docker. The role addresses complex production issues while improving platform reliability, security posture, and cost efficiency through automation.

What you'll do

  • Design, build, and operate scalable Kubernetes-based platform capabilities for development, test, and production workloads.
  • Create reusable infrastructure-as-code modules and automated workflows using tools like Terraform, Ansible, Helm, or Kustomize.
  • Develop and evolve platform observability systems including metrics, logs, traces, dashboards, and alerting.
  • Build the infrastructure required to deploy, operate, and govern AI/ML workloads and GPU-enabled compute.
  • Enable self-service for engineering teams through well-designed platform APIs, templates, and CI/CD integrations.
  • Improve platform reliability, security posture, and cost efficiency through automation and data-driven practices.
  • Investigate complex production issues and lead root-cause analysis to implement durable preventative improvements.
  • Contribute to technical roadmaps, architecture reviews, and engineering standards for the internal developer platform.

What we're looking for

  • Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
  • 6+ years of experience in software engineering, DevOps, SRE, cloud infrastructure, or platform engineering.
  • Strong hands-on experience operating and automating Kubernetes environments.
  • Experience with container technologies and deployment tooling such as Docker, Helm, Kustomize, Argo CD, Flux, or similar.
  • Experience implementing infrastructure as code using Terraform, Pulumi, CloudFormation, Ansible, or comparable tools.
  • Practical experience with observability platforms and concepts including metrics, logging, distributed tracing, alerting, dashboards, and SLOs.
  • Proficiency in at least one programming or scripting language such as Python, Go, Bash, or TypeScript.
  • Experience with CI/CD systems, automated software delivery, and troubleshooting across Linux, networking, and distributed systems.
  • Experience designing internal developer platforms or large-scale shared infrastructure (preferred).
  • Experience with Prometheus, Python, Bash, Grafana, OpenTelemetry, Loki, Tempo, Elastic, Datadog, Splunk, or comparable observability systems (preferred).
  • Experience with IBM LSF and Netapp Storage (preferred).
  • Experience with GitOps operating models (preferred).
  • Experience supporting AI/ML infrastructure, model serving, GPU scheduling, Kubernetes operators, or AI workload orchestration (preferred).
  • Knowledge of platform security practices including IAM, secrets management, policy enforcement, image security, and supply-chain security (preferred).
  • Experience with service mesh, API gateways, ingress, networking, or multi-cluster Kubernetes architectures (preferred).
  • Semiconductor experience very helpful; EDA experience a plus (preferred).

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