Senior Principal Big Data Engineer

Company:

SAIC Location:

San Diego, CA Career Level:

Mid-Senior Level Industries:

Technology, Software, IT, Electronics Description Description SAIC is seeking a visionary Senior Principal Big Data Engineer to support and expand our autonomous systems portfolio. This senior-level role requires a rare combination of strategic technology leadership, hands-on AI/ML delivery, enterprise-scale server infrastructure management. The successful candidate will contribute to the growth of the while driving path-breaking ML/AI solutions and ensure the highest levels of server infrastructure availability, performance, and security. The ideal candidate brings proven IT leadership, a demonstrated history of delivering first-of-kind technology solutions, and the analytical mindset of a strategic visionary capable of operating at both the executive and technical levels across massive server environments. This is a Hybrid/Remote role with expectations to be On-Site throughout the week in San Diego, CA. Must be local to area.

JOB DUTIES

Autonomous Systems & AI/ML Lead design and implementation of ML/AI solutions supporting autonomous systems programs. Drive Big Data analytics frameworks enabling real-time autonomous decision-making pipelines. Apply predictive modeling expertise — including high-frequency algorithmic model development — to autonomous system response and decision architectures. Develop and maintain autonomous systems data pipelines integrating server-side compute resources with edge autonomous platforms. Server Infrastructure Management & Support Plan, deploy, and manage scalable server environments supporting autonomous systems compute workloads, drawing on proven experience. Oversee end-to-end server lifecycle management including procurement, provisioning, configuration, patching, performance tuning, and decommissioning. Implement and maintain high-availability (HA) and disaster recovery (DR) architectures for mission-critical autonomous systems server infrastructure. Manage physical and virtual server environments including bare-metal, VMware, Hyper-V, and containerized workloads supporting DoD program requirements. Drive server utilization optimization strategies leveraging allocation-to-utilization based models, achieving measurable efficiency improvements across server fleets. Administer and support Redhat, Linux (RHEL/CentOS/Ubuntu) environments in classified and unclassified network enclaves. Support server hardening and STIG compliance across all managed server assets in accordance with DoD cybersecurity requirements as required. Monitor server health, performance metrics, and capacity planning using enterprise monitoring tools (SolarWinds, Nagios, Splunk, or equivalent). Manage storage area networks (SAN), NAS, and direct-attached storage (DAS) solutions supporting petabyte-scale data requirements. Support GPU server infrastructure for AI/ML training and inference workloads critical to autonomous systems development. Coordinate with network engineering teams to ensure optimal server-to-network integration across classified and unclassified environments. Maintain server asset inventory and configuration management databases (CMDB) in compliance with DoD IT asset management standards. Data Center & Infrastructure Operations Manage Data Center operations supporting autonomous systems compute requirements including CUI (Controlled Unclassified Information) compliance and physical security. Implement Infrastructure as Code (IaC) practices using Ansible, Terraform, or equivalent tools for automated server provisioning and configuration management as required. Drive cloud-hybrid server strategies integrating on-premises server infrastructure with Microsoft Azure and other cloud platforms. Manage server backup and recovery solutions ensuring data integrity and business continuity for autonomous systems program data. Support data center relocation and consolidation initiatives leveraging experience with portable, deployable server infrastructure. Ensure compliance with 

FISMA, RMF

(Risk Management Framework), and DoD 8570 requirements across all server infrastructure. Program & Stakeholder Management Support a cross-functional teams across software, data engineering, server administration, mechanical, and electrical disciplines in a matrix organization environment. Prepare and deliver technical briefings on server infrastructure status, capacity planning, and modernization roadmaps to internal and external stakeholders including Federal and DoD entities. Support RFP development and proposal responses for autonomous systems and server infrastructure opportunities. Develop and maintain server infrastructure documentation including architecture diagrams, standard operating procedures (SOPs), and continuity of operations plans (COOP). Innovation & Emerging Technology Research, prototype, and deliver cutting-edge autonomous and AI-driven technologies leveraging next-generation server platforms. Evaluate and recommend emerging server technologies including ARM-based servers, composable infrastructure, and software-defined data center (SDDC) solutions. Provide technical thought leadership on server infrastructure and autonomous systems capability gaps informing strategic investment decisions. Leverage IoT, NFC, and RFID sensor integration experience to support autonomous platform server-side data ingestion and processing. Drive adoption of DevSecOps practices across server infrastructure supporting autonomous systems CI/CD pipelines. Qualifications 

REQUIRED QUALIFICATIONS

Experience:

14+ years in senior IT/technology leadership roles.

Server Administration:

10+ years managing large-scale enterprise server environments (1,000+ servers).

AI/ML:

Hands-on ML/AI solution implementation in production server environments.

DoD Experience:

Prior NAVAIR or equivalent DoD program support.

Cloud Platforms:

Microsoft Azure, AWS, or equivalent hybrid cloud experience.

Virtualization:

VMware vSphere, Microsoft Hyper-V, or equivalent.

OS Proficiency:

Windows Server 2016/2019/2022, RHEL, CentOS, Ubuntu.

Storage:

SAN, NAS, and object storage management at petabyte scale.

Program Scale:

Demonstrated management of programs valued at $500M+.

Clearance:

Active Secret Clearance.

Education:

Bachelor of Science Degree or equivalent.

REQUIRED CERTIFICATIONS

Certified Dataiku ML/AI Practitioner Project Management Professional (PMP) ITIL Foundation Security+ OCP (Oracle Certified Professional) MCSE (Microsoft Certified Solutions Expert) CNE (Certified Novell Engineer) MCP (Microsoft Certified Professional)

Preferred Additional Certifications:

VMware Certified Professional (VCP) Red Hat Certified Engineer (RHCE) AWS Solutions Architect Microsoft Azure Administrator (AZ-104) CompTIA Server+ DoD 8570 IAT Level II or

III PREFERRED QUALIFICATIONS

Prior experience in technology organizations with direct server infrastructure oversight. Experience designing and deploying containerized server solutions for rapid deployment in austere or forward-operating environments. Familiarity with change data capture (CDC) methodologies across heterogeneous server and database environments. Experience with GPU cluster management for AI/ML training workloads. Background in high-frequency trading (HFT) infrastructure requiring ultra-low latency server configurations. Familiarity with DoD RMF accreditation processes for server systems.

SERVER INFRASTRUCTURE TECHNICAL COMPETENCIES

Server Platforms:

Dell PowerEdge, HP ProLiant, IBM Power, Cisco UCS Virtualization:

VMware v

Sphere/vCenter, Microsoft Hyper-V, KVM Containerization:

Docker, Kubernetes, OpenShift Operating Systems:

Windows Server, RHEL, CentOS, Ubuntu, AIX Storage:

NetApp, EMC/Dell, Pure Storage, IBM Spectrum Monitoring:

SolarWinds, Nagios, Splunk, Dynatrace Automation:

Ansible, Terraform, PowerShell, Bash Cloud Integration:

Microsoft Azure, AWS GovCloud, DoD Cloud Backup/Recovery:

Veeam, Commvault, Veritas NetBackup Security/Compliance:

STIG, FISMA, RMF, CUI, NIST 800-53

Target salary range: $160,001 - $200,000. The estimate displayed represents the typical salary range for this position based on experience and other factors.