You will be taken to AMD’s own careers page to apply. Job ID 92826.
Job description
ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology 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 AMD is shaping the future.
Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.
Lead DevOps Platform Engineer
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
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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.
#LI-SG2
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.
Responsibilities
Lead DevOps Platform Engineer
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.
