THE ROLE:
AMD's SW Ecosystem Security Engineering Team is seeking a software engineer to help deliver container orchestration and confidential computing infrastructure enabled by AMD Secure Encrypted Virtualization (SEV). In this role, the developer will design, implement, debug, and validate Rust and Go software that enables AMD confidential computing capabilities across Kubernetes, Kata Containers, Confidential Containers (CoCo), VirTEE, and related attestation technologies. The developer will work directly with open source communities by contributing code and tests upstream, participating in technical discussions and design reviews, responding to maintainer feedback, and helping align AMD platform enablement work with community roadmaps and standards. The role requires a strong understanding of virtualization, container orchestration, Linux systems, and server architecture, including how processor topology, NUMA characteristics, and hardware capabilities influence performance, orchestration, placement, and deployment of modern cloud-native workloads. The work spans the full software development lifecycle, with a focus on advancing AMD EPYC confidential computing infrastructure through secure, scalable, and production-ready software.

THE PERSON:
A highly motivated and passionate professional with deep technical expertise and a proven track record developing and delivering cloud-native infrastructure, container orchestration platforms, secure virtualization, and confidential computing solutions. The ideal candidate combines strong Kubernetes and Linux systems knowledge with a solid understanding of server architecture, NUMA behavior, processor topology, and AMD EPYC platform capabilities. This individual should be comfortable translating hardware features such as SEV-SNP, attestation technologies, memory isolation, cache hierarchy, CCD/CCX organization, chiplet architecture, and topology-aware scheduling considerations into robust software solutions for Kubernetes, Kata Containers, Confidential Containers, VirTEE, Trustee, and related open source projects. The successful candidate will play a key role in advancing AMD's confidential computing roadmap through upstream open source development, platform enablement, and the delivery of orchestration technologies that improve performance, scalability, workload placement, and operational efficiency on AMD EPYC-based infrastructure.

KEY RESPONSIBILITIES:
The primary focus of this role is designing, developing, validating, and enabling Kubernetes-based orchestration solutions for AMD EPYC confidential computing platforms. The engineer will drive the integration of AMD SEV technologies into cloud-native infrastructure, with particular emphasis on Kubernetes, Confidential Containers (CoCo), Kata Containers, attestation services, and related platform software. A significant portion of the role involves developing orchestration capabilities that improve deployment, scheduling, resource management, performance, and operational scalability for confidential workloads running on AMD EPYC systems. The position also requires a strong understanding of processor topology and platform architecture, including NUMA locality, CCD/CCX organization, cache hierarchy, SMT placement, and device affinity, and how those characteristics can be leveraged to improve containerized workload placement and infrastructure utilization.

Key areas of focus include:

• Enable and enhance AMD SEV-SNP capabilities within Kubernetes-based confidential computing platforms, including Confidential Containers (CoCo), Kata Containers, attestation services, and related infrastructure components.
• Develop software, integrations, and validation frameworks that improve the deployment, operation, security, and scalability of confidential workloads on Kubernetes and other container orchestration platforms.
• Design and implement topology-aware orchestration capabilities that leverage AMD EPYC architecture characteristics such as NUMA locality, CCD/CCX topology, cache hierarchy, SMT placement, memory affinity, and device locality to improve workload placement and performance.
• Integrate and validate AMD EPYC platform capabilities with Kubernetes resource-management technologies, including CPU Manager, Topology Manager, Memory Manager, Dynamic Resource Allocation (DRA), NRI, device plugins, and related scheduling and placement frameworks.
• Develop and maintain functional, interoperability, performance, scalability, and topology-awareness test suites for Kubernetes, Confidential Containers, and AMD confidential computing infrastructure.
• Debug and optimize complex software stacks spanning Kubernetes, container runtimes, Linux, KVM/QEMU, guest firmware, attestation services, hardware topology, and platform resource-management layers.
• Contribute code, tests, documentation, and technical guidance to selected open-source projects where necessary to support AMD platform enablement and confidential computing objectives.
• Support related confidential computing infrastructure projects, including Trustee, VirTEE, and other attestation technologies, as required to enable end-to-end platform functionality.

PREFERRED EXPERIENCE:

• Strong software development experience in Go, Rust, Python, and Bash with a focus on cloud-native infrastructure, distributed systems, systems software, virtualization, or container platforms.
• Deep technical expertise with Kubernetes and container orchestration, including cluster architecture, scheduling, resource management, workload placement, networking, storage, observability, and production deployment of containerized workloads.
• Hands-on experience developing or integrating with Kubernetes ecosystem technologies such as KubeVirt, OpenShift Virtualization, Red Hat OpenShift, container runtimes, schedulers, operators, device plugins, NRI, DRA, CPU Manager, Topology Manager, Memory Manager, or similar cloud-native infrastructure components.
• Strong understanding of AMD EPYC and modern server architecture, including NUMA topology, CCD/CCX organization, cache hierarchy, SMT behavior, memory locality, PCIe topology, accelerator placement, CPU pinning, and workload-performance optimization.
• Experience designing or implementing topology-aware resource-management solutions that improve workload placement, scaling efficiency, infrastructure utilization, performance consistency, or operational predictability in Kubernetes and virtualized environments.
• Technical proficiency with Linux, KVM, QEMU, libvirt, guest firmware, virtualization infrastructure, VM lifecycle management, performance analysis, and platform debugging across host, guest, hypervisor, and container layers.
• Experience with confidential computing technologies such as AMD SEV-SNP, SEV, confidential VMs, confidential containers, attestation services, trusted execution environments, or hardware-assisted workload isolation technologies.
• Experience developing platform validation frameworks, CI environments, end-to-end tests, performance benchmarks, scalability testing, hardware-backed validation, or solution-enablement demonstrations for infrastructure software.
• Experience collaborating with operating system vendors, cloud providers, software partners, hardware engineering teams, customers, or open-source communities to enable new platform capabilities and bring infrastructure features into production environments.
• Working knowledge of attestation technologies, policy enforcement, workload identity, secret-release workflows, certificate management, or related security technologies used in confidential computing environments.
• Experience contributing code, reviews, tests, documentation, design proposals, or technical leadership to open-source projects is desirable.

ACADEMIC CREDENTIALS:

• Bachelor's or Master's degree in Computer or Electrical Engineering or equivalent

LOCATION:

Austin, TX or Santa Clara, CA

THIS ROLE IS NOT ELIGIBLE FOR VISA SPONSORSHIP.

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