[Hiring] Network and Compute Engineer, AI Infrastructure @Apptad, Inc.

Role Description

The Network and Compute Engineer will design, deploy, validate, and operate high-performance infrastructure supporting enterprise artificial intelligence and accelerated-computing workloads. The engineer will work across various domains including:

• Compute
• Networking
• Operating systems
• Container orchestration
• Cluster management
• Storage integration
• Security
• Observability

The successful candidate will be comfortable working hands-on with complex infrastructure, diagnosing issues across multiple technical layers, and translating platform requirements into reliable and repeatable operational solutions.

The role is aligned to an NVIDIA AI Factory environment, covering:

• NVIDIA Mission Control
• Base Command Manager
• Kubernetes installation
• Rack management
• Bare-metal management
• Observability
• Run:ai
• MGX architecture
• Slurm
• GB200 software and firmware
• NVLink partitioning
• XID troubleshooting
• Telemetry

Qualifications

• Bachelor's degree in computer science, information technology, electronics, telecommunications, or a related field, or equivalent practical experience.
• 7 or more years of experience in infrastructure, compute, network, data-center, cloud-platform, or high-performance-computing engineering.
• 3 or more years of hands-on experience with Linux-based cluster platforms, Kubernetes, accelerated computing, or comparable large-scale infrastructure.
• Demonstrated experience owning complex technical problems from initial diagnosis through resolution and prevention.

Requirements

• Strong administration and troubleshooting experience with Linux.
• Strong knowledge of data-center networking, including Ethernet, TCP/IP, routing, switching, VLANs, link aggregation, DNS, DHCP, and NTP.
• Hands-on experience installing or operating Kubernetes clusters.
• Experience deploying and supporting physical compute infrastructure.
• Understanding of server boot processes, operating-system imaging, firmware, device drivers, hardware management, and remote management controllers.
• Experience diagnosing issues across server, operating-system, network, and application layers.
• Working knowledge of Python, Bash, Ansible, or equivalent infrastructure-automation technologies.
• Experience with monitoring, logging, metrics, dashboards, alerting, and telemetry.
• Ability to create clear architecture diagrams, build documents, operating procedures, and troubleshooting runbooks.
• Strong analytical skills and the ability to work effectively during complex infrastructure incidents.

Benefits

• Certifications are desirable but should not replace proven hands-on capability.
• NVIDIA Certified Associate or NVIDIA Certified Professional credentials relevant to AI infrastructure.
• Red Hat Certified System Administrator or Red Hat Certified Engineer.
• Certified Kubernetes Administrator.
• Cisco Certified Network Professional, Data Center or Enterprise.
• NVIDIA networking or InfiniBand training.
• Linux Foundation certifications.
• Security-focused credentials appropriate to the operating environment.

Measures of Success

• Successful, repeatable cluster and node deployments.
• High availability and operational stability of network and compute platforms.
• Reduced build time through automation and reusable configurations.
• Faster detection, diagnosis, and recovery from infrastructure failures.
• Lower configuration drift and fewer manual deployment errors.
• Complete operational documentation and effective knowledge transfer.
• Timely remediation of security vulnerabilities and unsupported firmware or software.
• Efficient use of expensive accelerated-compute capacity.
• Positive customer and stakeholder outcomes during deployments and production operations.