Job Description

Salary: $88,000 - 128,000 per year Requirements:

• Bachelors degree in Computer Engineering, Electrical Engineering, or equivalent work experience
• Minimum of 12 years of experience in systems engineering, focusing on Linux administration and high-performance computing (HPC)
• Experience managing petabyte-scale storage systems (NAS, SAN, Object Storage) and parallel file systems (e.g., Lustre, GPFS, Isilon, NetApp) in research or clinical environments
• Deep expertise in networking optimization for data-intensive workloads (10GbE/40GbE/100GbE, RDMA, TCP/IP tuning)
• Proficiency in designing hybrid infrastructure that connects on-premise data centers with public cloud providers (Azure, AWS)
• Knowledge of supporting biomedical instrumentation, imaging pipelines, or genomics workflows
• Mastery of Linux kernel tuning, storage I/O subsystems, and hardware architecture (CPU/GPU/RAM interactions)
• Ability to automate system administration and data movement tasks using Python, Bash, or similar scripting languages
• Experience configuring and managing job schedulers and workload managers (e.g., Slurm, LSF, Grid Engine) for optimal resource allocation
• Strong network engineering skills, including switching, routing, and firewall configuration for high-throughput scientific data
• Demonstrated problem-solving ability to troubleshoot complex hardware and software bottlenecks in distributed systems

• Design, deploy, and maintain on-premise high-performance computing clusters and scientific storage solutions optimized for large-scale biomedical data
• Optimize the write path for critical lab instruments (digital pathology scanners, NGS sequencers) to prevent data bottlenecks during high-volume acquisition
• Develop automated data lifecycle policies for efficient data movement between local processing tiers, on-premise retention, and cloud archival, balancing performance and cost
• Establish and maintain secure high-bandwidth connectivity (e.g., Direct Connect, ExpressRoute) between on-premise infrastructure and cloud environments (Azure, AWS), collaborating with Cloud DevOps teams to support hybrid workflows
• Monitor and adjust file system performance (I/O profiling), network latency, and job scheduler configurations to meet strict Service Level Agreements (SLAs) for lab turnaround times
• Lead the technical evaluation, specification, and procurement of specialized compute hardware (GPU nodes for inference) and storage arrays as data volumes grow
• Implement robust local backup and disaster recovery strategies for raw instrument data to uphold data integrity and business continuity prior to cloud replication
• Collaborate with Lab Operations and Engineering teams to resolve complex hardware-software interaction issues at the instrument level
• Ensure compliance of all on-premise scientific infrastructure with stringent security standards (encryption at rest and in transit) and regulatory requirements (HIPAA, GxP)

• AWS
• Azure
• Bash
• Cloud
• DevOps
• Firewall
• Hardware
• Support
• Linux
• Network
• Python
• RDMA
• REST
• Security
• TCP/IP
• AI
• Flow

More:

At NeoGenomics, we are committed to fostering a dynamic and multi-tasking environment where every employee can thrive and grow. We believe in investing in our team by providing internal career coaches and numerous training opportunities for knowledge expansion. Our competitive benefits include a variety of HMO and PPO options, a 401k match, tuition reimbursement, leadership development, and an initial offering of 16 days of paid time off in addition to holidays. We actively promote wellness initiatives and have engaging employee resource groups. Join our team in Aliso Viejo, CA as a Senior Systems Engineer, and help us improve patient care through your exceptional work in our mission to be the worlds leading cancer reference laboratory.

last updated 13 week of 2026

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