Platform Engineer: Kubernetes & AI Workloads

Advanced Micro Devices; San Jose (CA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

AMD Benefits

Job summary

Advanced Micro Devices, Inc. (AMD) is seeking a hands-on Platform Engineer in San Jose to design, build, and operate a scalable internal platform.

You will work across Kubernetes, CI/CD, observability, and AI/ML workloads to provide a reliable, secure developer experience. The ideal candidate has 6+ years in platform engineering or related fields, strong Kubernetes ops skills, and hands‑on experience with Terraform, Argo CD, Prometheus, Grafana, and open source tooling.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or related 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.
• Observability platforms and concepts: metrics, logging, tracing, alerting, dashboards, and SLOs.
• Programming or scripting in Python, Go, Bash, or TypeScript.
• Experience with CI/CD systems and automated software delivery practices.
• Strong troubleshooting across Linux, networking, containers, cloud or on‑premise infrastructure, and distributed systems.

Responsibilities

• 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 Terraform, Ansible, Helm, Kustomize, or equivalent tools.
• Develop and evolve platform observability: metrics, logs, traces, dashboards, alerting, SLOs.
• Improve platform reliability, capacity, security posture, and cost efficiency through automation.
• Build infrastructure to deploy AI/ML workloads, including model‑serving and GPU‑enabled compute.
• Enable self‑service for product teams via platform APIs, templates, and CI/CD integrations.
• Collaborate with security, infrastructure, and AI teams to define standards and remove bottlenecks.
• Investigate production issues, perform root cause analysis, and implement preventive improvements.
• Contribute to roadmaps, architecture reviews, and engineering standards.

Skills

Kubernetes

Python

Go

CI/CD

Linux

Communication

Education

Bachelors in CS/Engineering

Tools

Terraform

Ansible

Helm

Kustomize

Argo CD

Flux

Prometheus

Grafana

OpenTelemetry

Job description

ADVANCE YOUR CAREER. ADVANCE THE WORLD.

At AMD, we believetechnology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMDis shapingthefuture.

Whetheryou’redesigning next-gen processors, enabling AI breakthroughs, orbringing leading edge products to market, every role at AMD contributes to something bigger— technologythat moves the world forward.Join us and, together, we’ll advance your career.

THE ROLE:

We are seeking a hands-on Platform Engineer to build and operate the infrastructure foundations that enable engineering teams to deliver reliable, scalable, and secure products. This role will shape the internal developer platform across Kubernetes, observability, AI-enabled workloads, CI/CD, and infrastructure as code.

You will work closely with software, DevOps, security, and AI/ML teams to turn platform capabilities into a simple and dependable developer experience. The ideal candidate is comfortable moving between architecture decisions, production operations, automation, and practical enablement of partner teams.

KEY RESPONSIBILITIES:

• Design, build, and operate scalable Kubernetes-based platform capabilities for development, test, and production workloads.
• Create reusable infrastructure-as-code modules, patterns, and automated workflows using tools such as Terraform, Ansible, Helm, Kustomize, or equivalent technologies.
• Develop and evolve platform observability: metrics, logs, traces, dashboards, alerting, service-level objectives, and operational runbooks.
• Improve platform reliability, capacity management, security posture, and cost efficiency through automation and data-driven operational practices.
• Build the infrastructure required to deploy, operate, observe, and govern AI/ML workloads, including model-serving, GPU-enabled compute, data-access, and workload-isolation patterns where applicable.
• Enable self-service for product and engineering teams through well-designed platform APIs, templates, documentation, golden paths, and CI/CD integrations.
• Partner with application, security, infrastructure, and AI teams to define platform standards and remove delivery bottlenecks.
• Investigate complex production issues, lead root-cause analysis, and implement durable preventative improvements.
• Contribute to technical roadmaps, architecture reviews, and engineering standards for the platform.

PREFERRED EXPERIENCE:

• Experience designing internal developer platforms or large-scale shared infrastructure.
• Experience with Prometheus, Python, Bash, Grafana, OpenTelemetry, Loki, Tempo, Elastic, Datadog, Splunk, or comparable observability systems.
• Experience with IBM LSF and Netapp Storage
• Experience with GitOps operating models.
• Experience supporting AI/ML infrastructure, model serving, GPU scheduling, Kubernetes operators, or AI workload orchestration.
• Knowledge of platform security practices, including identity and access management, secrets management, policy enforcement, image security, and supply-chain security.
• Experience with service mesh, API gateways, ingress, networking, or multi-cluster Kubernetes architectures.
• Demonstrated ownership of production systems and a bias toward automation, operational excellence, and continuous improvement.
• Semiconductor experience very helpful, EDA experience a plus.

Required Qualifications

• 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 and automated software delivery practices.
• Strong troubleshooting skills across Linux, networking, containers, cloud or on‑premise infrastructure, and distributed systems.
• Clear written and verbal communication skills, with an ability to work effectively across engineering disciplines.

This role is not eligible for visa sponsorship.

Benefits offered are described: AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee‑based recruitment services. AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third‑party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position. AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.