Infrastructure Engineer Jobs in San Jose, CA
Infrastructure Engineer jobs in San Jose are concentrated in North San Jose, Downtown, and the Alviso corridor, where semiconductor, cloud infrastructure, and enterprise software companies drive steady demand for network, systems, and cloud infrastructure talent. Employers hiring right now include TikTok, ByteDance, and AMD. Find a role that fits below and apply directly.
Find Infrastructure Engineer JobsOverview
Open roles657+
Top employerTikTok
Work type72% On-site
Top credentialMaster's degree
Companies hiring26
Showing 5 of 657+ Infrastructure Engineer jobs
HPC & AI Infrastructure Engineer
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Added 1d ago
AMD
HPC & AI Infrastructure Engineer
San Jose, California
Added 1d ago
DevOps & IT Infrastructure Engineer
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Added 6d ago
TetraMem INC
DevOps & IT Infrastructure Engineer
San Jose, California
Added 6d ago
Machine Learning Infrastructure Engineer
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Added 6d ago
TikTok USDS Joint Venture
Machine Learning Infrastructure Engineer
San Jose, California
Added 6d ago
Cloud Infrastructure Engineer
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Added 1w ago
Lorven Technologies Inc.
Cloud Infrastructure Engineer
San Jose, California
Added 1w ago
Sr. Solutions Architect/Sales Engineer-AI Infrastructure (GPU) -West Coast
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Added 1w ago
LIQID
Sr. Solutions Architect/Sales Engineer-AI Infrastructure (GPU) -West Coast
San Jose, California
Added 1w ago
Added 1d ago
HPC & AI Infrastructure Engineer
AMD·San Jose, California
Job functions:
Master's degree
5,001-10,000 employees
Job Description
Overview:
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.
Responsibilities:
THE PERSON:
KEY RESPONSIBILITIES:
PREFERRED EXPERIENCE:
ACADEMIC CREDENTIALS:
This role is not eligible for visa sponsorship.
#LI-DP1
Qualifications:
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.
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.
THE ROLE:
We are seeking an HPC & AI Infrastructure Engineer to join AMD IT’s Compute Platforms Engineering team. You will help design, deploy, automate, and operate CPU and GPU infrastructure supporting high-performance computing, distributed AI training, and inference workloads across on-premises and cloud environments.
This role involves delivering infrastructure engineering projects, troubleshooting complex systems issues, and improving platform performance, scalability, and reliability. You will collaborate with architects, operations teams, researchers, network engineers, cloud partners, and technology vendors to bring new capabilities into production.
THE PERSON:
You enjoy solving complex systems problems and building reliable infrastructure. You approach troubleshooting using data and systematic analysis and look for opportunities to simplify operations through automation. You can work effectively both independently and collaboratively, communicate technical information clearly, and partner with colleagues across functions, regions, and time zones. You are comfortable seeking input when decisions affect broader platform architecture or other teams.
KEY RESPONSIBILITIES:
- Deploy, configure, and maintain Linux-based CPU and GPU clusters following established architecture and security standards.
- Administer Slurm and Kubernetes environments, including scheduling, resource allocation, access controls, and workload troubleshooting.
- Support distributed AI training and inference platforms by managing software environments, containers, and workload deployments.
- Automate infrastructure provisioning, configuration, and lifecycle management using infrastructure as code, configuration management, and scripting.
- Validate hardware, BIOS, firmware, GPU drivers, and runtime compatibility and support upgrades through testing, rollback planning, and user communication.
- Configure and troubleshoot host networking for HPC and GPU workloads, including high-speed NICs, RDMA interfaces, IP addressing, VLANs, MTU settings, and routing.
- Partner with network engineering teams to deploy and validate RoCEv2 or InfiniBand fabrics, including connectivity, congestion management, and end-to-end RDMA performance.
- Troubleshoot issues across compute, GPU, networking, storage, virtualization, and container environments.
- Conduct cluster acceptance testing and workload benchmarking to identify bottlenecks and improve performance, utilization, and reliability.
- Implement monitoring, dashboards, and alerts and contribute to incident resolution, root-cause analysis, and preventive improvements.
- Apply security updates and support vulnerability remediation in partnership with security and operations teams.
- Create and maintain technical documentation, operating procedures, and deployment runbooks.
- Collaborate with infrastructure partners, cloud providers, and hardware vendors to deliver projects and resolve technical issues.
PREFERRED EXPERIENCE:
Candidates are not expected to have experience with every technology listed below. Relevant skills may be developed through professional experience, education, training, or other technical pathways.
- Experience supporting Linux systems, HPC infrastructure, cloud platforms, GPU infrastructure, or distributed computing environments.
- Experience deploying, configuring, supporting, or operating HPC or GPU clusters.
- Linux administration and troubleshooting experience across operating systems, networking, storage, and system performance.
- Experience with Slurm, Kubernetes, or comparable workload scheduling and orchestration platforms.
- Experience supporting GPU drivers, containerized GPU workloads, or accelerator software stacks. Familiarity with AMD Instinct GPUs, ROCm, RCCL, or comparable technologies is beneficial.
- Familiarity with distributed computing concepts such as MPI, collective communication, and multi-node training.
- Experience working with high-speed Ethernet, InfiniBand, or comparable cluster networking technologies.
- Familiarity with RDMA and RoCEv2 concepts, including queue pairs, priority flow control (PFC), explicit congestion notification (ECN), and their relationship to fabric performance.
- Familiarity with leaf-spine topologies, fabric oversubscription, ECMP, and the impact of network latency, bandwidth, and congestion on distributed workloads.
- Experience troubleshooting or supporting high-speed cluster interconnects such as RoCEv2 or InfiniBand.
- Familiarity with Kubernetes networking technologies for GPU workloads, including CNI plugins, SR-IOV, or RDMA device plugins, is beneficial.
- Experience with shared or parallel storage technologies such as NFS, Lustre, BeeGFS, IBM Storage Scale, Weka, or comparable technologies.
- Experience using Python, Bash, or comparable scripting languages for infrastructure automation.
- Familiarity with configuration management and infrastructure-as-code technologies such as Ansible, SaltStack, Terraform, or comparable tools.
- Experience with Git-based workflows and monitoring or observability technologies such as Prometheus, Grafana, or comparable platforms.
- Experience with cloud infrastructure such as OCI, Microsoft Azure, AWS, specialized GPU cloud providers, or comparable environments.
- Familiarity with virtualization technologies such as KVM is beneficial.
- Familiarity with AI frameworks and inference technologies such as PyTorch, vLLM, SGLang, or comparable technologies is beneficial.
- Ability to troubleshoot complex technical issues, organize competing priorities, communicate technical information clearly, and collaborate across engineering and operations teams.
ACADEMIC CREDENTIALS:
- Bachelor’s or master’s degree in computer science, Computer Engineering, or a related field or an equivalent combination of education and relevant professional experience.
This role is not eligible for visa sponsorship.
#LI-DP1
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.
AMD
HPC & AI Infrastructure Engineer
San Jose, California
Added 1d ago5,001-10,000 employees
Job functions:
Master's degree
Job Description
Overview:
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.
Responsibilities:
THE PERSON:
KEY RESPONSIBILITIES:
PREFERRED EXPERIENCE:
ACADEMIC CREDENTIALS:
This role is not eligible for visa sponsorship.
#LI-DP1
Qualifications:
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.
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.
THE ROLE:
We are seeking an HPC & AI Infrastructure Engineer to join AMD IT’s Compute Platforms Engineering team. You will help design, deploy, automate, and operate CPU and GPU infrastructure supporting high-performance computing, distributed AI training, and inference workloads across on-premises and cloud environments.
This role involves delivering infrastructure engineering projects, troubleshooting complex systems issues, and improving platform performance, scalability, and reliability. You will collaborate with architects, operations teams, researchers, network engineers, cloud partners, and technology vendors to bring new capabilities into production.
THE PERSON:
You enjoy solving complex systems problems and building reliable infrastructure. You approach troubleshooting using data and systematic analysis and look for opportunities to simplify operations through automation. You can work effectively both independently and collaboratively, communicate technical information clearly, and partner with colleagues across functions, regions, and time zones. You are comfortable seeking input when decisions affect broader platform architecture or other teams.
KEY RESPONSIBILITIES:
- Deploy, configure, and maintain Linux-based CPU and GPU clusters following established architecture and security standards.
- Administer Slurm and Kubernetes environments, including scheduling, resource allocation, access controls, and workload troubleshooting.
- Support distributed AI training and inference platforms by managing software environments, containers, and workload deployments.
- Automate infrastructure provisioning, configuration, and lifecycle management using infrastructure as code, configuration management, and scripting.
- Validate hardware, BIOS, firmware, GPU drivers, and runtime compatibility and support upgrades through testing, rollback planning, and user communication.
- Configure and troubleshoot host networking for HPC and GPU workloads, including high-speed NICs, RDMA interfaces, IP addressing, VLANs, MTU settings, and routing.
- Partner with network engineering teams to deploy and validate RoCEv2 or InfiniBand fabrics, including connectivity, congestion management, and end-to-end RDMA performance.
- Troubleshoot issues across compute, GPU, networking, storage, virtualization, and container environments.
- Conduct cluster acceptance testing and workload benchmarking to identify bottlenecks and improve performance, utilization, and reliability.
- Implement monitoring, dashboards, and alerts and contribute to incident resolution, root-cause analysis, and preventive improvements.
- Apply security updates and support vulnerability remediation in partnership with security and operations teams.
- Create and maintain technical documentation, operating procedures, and deployment runbooks.
- Collaborate with infrastructure partners, cloud providers, and hardware vendors to deliver projects and resolve technical issues.
PREFERRED EXPERIENCE:
Candidates are not expected to have experience with every technology listed below. Relevant skills may be developed through professional experience, education, training, or other technical pathways.
- Experience supporting Linux systems, HPC infrastructure, cloud platforms, GPU infrastructure, or distributed computing environments.
- Experience deploying, configuring, supporting, or operating HPC or GPU clusters.
- Linux administration and troubleshooting experience across operating systems, networking, storage, and system performance.
- Experience with Slurm, Kubernetes, or comparable workload scheduling and orchestration platforms.
- Experience supporting GPU drivers, containerized GPU workloads, or accelerator software stacks. Familiarity with AMD Instinct GPUs, ROCm, RCCL, or comparable technologies is beneficial.
- Familiarity with distributed computing concepts such as MPI, collective communication, and multi-node training.
- Experience working with high-speed Ethernet, InfiniBand, or comparable cluster networking technologies.
- Familiarity with RDMA and RoCEv2 concepts, including queue pairs, priority flow control (PFC), explicit congestion notification (ECN), and their relationship to fabric performance.
- Familiarity with leaf-spine topologies, fabric oversubscription, ECMP, and the impact of network latency, bandwidth, and congestion on distributed workloads.
- Experience troubleshooting or supporting high-speed cluster interconnects such as RoCEv2 or InfiniBand.
- Familiarity with Kubernetes networking technologies for GPU workloads, including CNI plugins, SR-IOV, or RDMA device plugins, is beneficial.
- Experience with shared or parallel storage technologies such as NFS, Lustre, BeeGFS, IBM Storage Scale, Weka, or comparable technologies.
- Experience using Python, Bash, or comparable scripting languages for infrastructure automation.
- Familiarity with configuration management and infrastructure-as-code technologies such as Ansible, SaltStack, Terraform, or comparable tools.
- Experience with Git-based workflows and monitoring or observability technologies such as Prometheus, Grafana, or comparable platforms.
- Experience with cloud infrastructure such as OCI, Microsoft Azure, AWS, specialized GPU cloud providers, or comparable environments.
- Familiarity with virtualization technologies such as KVM is beneficial.
- Familiarity with AI frameworks and inference technologies such as PyTorch, vLLM, SGLang, or comparable technologies is beneficial.
- Ability to troubleshoot complex technical issues, organize competing priorities, communicate technical information clearly, and collaborate across engineering and operations teams.
ACADEMIC CREDENTIALS:
- Bachelor’s or master’s degree in computer science, Computer Engineering, or a related field or an equivalent combination of education and relevant professional experience.
This role is not eligible for visa sponsorship.
#LI-DP1
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.
See All 657+ Infrastructure Engineer Jobs in San Jose
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Find Infrastructure Engineer JobsInfrastructure Engineer Job Market in San Jose
Who's Hiring
- TikTok175
- ByteDance123
- AMD31
- Etched31
- Google31
Top Industries Hiring
- Technology & Software82
- Consulting & Professional Services21
- Automotive10
- Electronics & Hardware10
Infrastructure Engineer Jobs in San Jose: Frequently Asked Questions
How do I get an infrastructure engineer job in San Jose?
The strongest path into San Jose infrastructure engineering runs through the city's semiconductor, cloud, and enterprise software sectors, which are concentrated in North San Jose and the Golden Triangle. Candidates who can demonstrate hands-on experience with large-scale distributed systems or hybrid cloud environments stand out. Targeting mid-size tech companies and hardware manufacturers alongside the large campus employers broadens your options considerably.
Which companies hire infrastructure engineers in San Jose?
Companies currently hiring infrastructure engineers in San Jose include TikTok, ByteDance, and AMD, per current listings on Migrate Mate as of November 2026. San Jose's mix of semiconductor giants, networking hardware firms, and enterprise SaaS companies means demand comes from both legacy infrastructure teams and modern cloud-native engineering organizations.
Are there remote infrastructure engineer jobs in San Jose?
Yes, though availability depends heavily on the role: hands-on data center, network hardware, and on-site lab positions are almost always in-person, while cloud architecture, SRE, and infrastructure automation roles are more remote-friendly. About 28% of infrastructure engineer openings tied to San Jose are remote or hybrid as of November 2026. Cloud and DevOps-focused infrastructure roles at San Jose's enterprise software companies offer the most flexibility.
How can I get an infrastructure engineer job in San Jose with little or no experience?
The most realistic entry point in San Jose is a junior systems administrator or IT operations role at one of the city's mid-size tech or hardware companies, which tend to hire for reliability and trainability over years of experience. Contract or temp-to-hire roles at local data centers in North San Jose and Alviso also provide a practical foot in the door. Certifications in AWS, Azure, or Cisco networking carry real weight with San Jose hiring managers.
Which industries hire the most infrastructure engineers in San Jose?
Most infrastructure engineer openings in San Jose sit in Technology & Software, Consulting & Professional Services, and Automotive, per current listings on Migrate Mate as of November 2026. San Jose's position as the center of Silicon Valley means semiconductor manufacturing, cloud platform development, and enterprise networking hardware all require deep, sustained infrastructure engineering capacity year-round.
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