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Job description
Leads development and begins architecting scalable, container-based services that build, validate, and monitor liquid-cooled GPU infrastructure across factory environments.
Develops secure infrastructure, control-plane workflows, and data-plane test capabilities that orchestrate manufacturing test lifecycles, operator workflows, quality gates, fleet status, and business reporting for platforms including GB200, GB300, VR, MI355, and MI455.
Automates and maintains GPU test validation; manages consistent firmware, software, and hardware configuration; and develops repair and triage capabilities that identify root causes and guide recovery.
Partners with Supply Chain Operations, Hardware Development, external manufacturing partners, data-center operations, NVIDIA, and AMD to resolve issues before racks ship.
Establishes manufacturing yield, throughput, quality, and deployment-readiness metrics that reduce rework and downstream failures, improve data-center ingestion, and accelerate reliable hyperscale AI infrastructure delivery.
Internal Responsibilities
Lead the design, implementation, and ongoing evolution of core distributed systems and data-plane services at hyperscale.
Define scalability, elasticity, durability, and availability requirements for owned components and ensure designs meet them.
Optimize high-throughput data paths for large-scale retrieval, storage, and processing using distributed state, replication, and synchronization patterns.
Design fault-tolerant systems that support in-service updates through redundancy, automatic failover, and recovery-oriented design.
Apply sound distributed-systems tradeoffs for network partitions and reliability, including load shedding, throttling, rate limiting, retries, and timeouts.
Establish service-level objectives, key performance indicators, telemetry, dashboards, and proactive alerting for critical systems.
Design and lead performance, load, fault-injection, and brownout testing to validate correctness, resilience, and operational readiness.
Lead production incident diagnosis and recovery, guide root-cause analysis, and mentor engineers in operational excellence.
Build and improve Infrastructure as Code and operational automation that enable safe patching, updates, rollbacks, and change management.
Apply robust security controls and remediation practices for multi-tenant cloud infrastructure, including encryption, access controls, and compliance readiness.
Qualifications
Bachelor's or master's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
7+ years of professional software-engineering experience, with demonstrated impact on large-scale distributed systems or cloud infrastructure.
Strong experience designing and operating highly available, scalable, fault-tolerant distributed systems.
Proficiency in one or more object-oriented or systems programming languages, such as Java, C++, C#, or Go.
Deep understanding of distributed-systems design, data structures, algorithms, operating systems, networking, and secure software-development practices.
Experience with system-level test automation, performance/load testing, reliability engineering, and production incident response.
Demonstrated experience leading or influencing technical architecture and mentoring engineers.
Strong problem-solving, communication, and cross-functional collaboration skills.
Preferred Qualifications
Experience with Oracle Cloud, AWS, Azure, Google Cloud, or other large-scale cloud platforms.
Experience with data-plane platforms, distributed storage, microservices, replication, state management, or high-throughput data processing.
Experience defining SLOs, building observability systems, and operating services in a 24x7 production environment.
Experience with Infrastructure as Code, service automation, security controls, and compliance requirements for cloud infrastructure.
External Responsibilities
Lead the design, implementation, and ongoing evolution of core distributed systems and data-plane services at hyperscale.
Define scalability, elasticity, durability, and availability requirements for owned components and ensure designs meet them.
Optimize high-throughput data paths for large-scale retrieval, storage, and processing using distributed state, replication, and synchronization patterns.
Design fault-tolerant systems that support in-service updates through redundancy, automatic failover, and recovery-oriented design.
Apply sound distributed-systems tradeoffs for network partitions and reliability, including load shedding, throttling, rate limiting, retries, and timeouts.
Establish service-level objectives, key performance indicators, telemetry, dashboards, and proactive alerting for critical systems.
Design and lead performance, load, fault-injection, and brownout testing to validate correctness, resilience, and operational readiness.
Lead production incident diagnosis and recovery, guide root-cause analysis, and mentor engineers in operational excellence.
Build and improve Infrastructure as Code and operational automation that enable safe patching, updates, rollbacks, and change management.
Apply robust security controls and remediation practices for multi-tenant cloud infrastructure, including encryption, access controls, and compliance readiness.
Qualifications
Bachelor's or master's degree in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
7+ years of professional software-engineering experience, with demonstrated impact on large-scale distributed systems or cloud infrastructure.
Strong experience designing and operating highly available, scalable, fault-tolerant distributed systems.
Proficiency in one or more object-oriented or systems programming languages, such as Java, C++, C#, or Go.
Deep understanding of distributed-systems design, data structures, algorithms, operating systems, networking, and secure software-development practices.
Experience with system-level test automation, performance/load testing, reliability engineering, and production incident response.
Demonstrated experience leading or influencing technical architecture and mentoring engineers.
Strong problem-solving, communication, and cross-functional collaboration skills.
Preferred Qualifications
Experience with Oracle Cloud, AWS, Azure, Google Cloud, or other large-scale cloud platforms.
Experience with data-plane platforms, distributed storage, microservices, replication, state management, or high-throughput data processing.
Experience defining SLOs, building observability systems, and operating services in a 24x7 production environment.
Experience with Infrastructure as Code, service automation, security controls, and compliance requirements for cloud infrastructure.
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Worksite address
nashville, TN, 37247, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.