Top Linux Jobs in San Diego, CA

Architect and develop embedded Android and Linux platforms for connected devices and industrial IoT solutions. Responsibilities include Android framework customization, system bring-up, BSP integration, hardware/software validation, kernel and HAL development, performance optimization, security enhancements, platform certification, and cross-layer troubleshooting. The role collaborates with hardware, firmware, systems, quality, and product teams and provides technical mentorship and customer-facing support.

Updates existing SolidWorks parts, assemblies, drawings, BOMs, and PDM records to improve engineering data accuracy and ERP readiness. Repairs file references, verifies assembly and drawing integrity, manages metadata and revisions, consolidates legacy files, and maintains controlled documentation while preserving design intent. Collaborates with engineering leads, performs peer reviews, resolves discrepancies, and completes repetitive data-management tasks according to established standards.

Designs, develops, and executes automated tests for Guidewire PolicyCenter applications. Builds and maintains Playwright automation frameworks, uses AI tools such as Microsoft Copilot and Claude to optimize test creation, manages defects, and collaborates with developers, business analysts, and stakeholders. Requires onsite work from day one in San Antonio, Plano, or Phoenix.

The Developer Solution Architect will evaluate and adopt a new data pipeline service, enhance developer experience, and support onboarding and technical initiatives.

Leads and performs advanced administration, design, maintenance, troubleshooting, and security for municipal network, server, cloud, virtualization, telecommunications, and identity infrastructure. Supervises IT staff, assigns work, mentors employees, supports budgeting and prioritization, and leads modernization, upgrades, and migrations. Provides escalation support for complex technical issues, maintains technical expertise, and participates in after-hours, weekend, and holiday support rotations.

Support mission-critical DoD Linux and VMware environments at NAWS China Lake. Responsibilities include securing and hardening RHEL systems with DISA STIGs, managing ACAS and Evaluate STIG assessments, maintaining VMware ESXi, automating administration with Ansible, applying updates, monitoring system health, and supporting RMF and ATO compliance. The role also involves Active Directory, DNS, documentation, vulnerability management, and collaboration with DevOps and security teams.

Supports the analysis, design, configuration, testing, deployment, and ongoing support of information systems. Elicits and documents requirements, analyzes workflows, develops proof-of-concept code, troubleshoots issues, maintains documentation, assists with reporting and data analysis, and ensures data integrity. Collaborates with stakeholders, developers, QA teams, and project managers under the guidance of senior team members while developing technical and business expertise.

Design and build scalable frontend features and reusable UI components using React and TypeScript. Collaborate with PMs, designers, and backend engineers on architecture, state management, API integration, performance, accessibility, and testing. Drive best practices for CI/CD, code quality, documentation, planning, and user experience.

Owns high-severity customer reliability issues across cloud infrastructure, Kubernetes, Linux, networking, IAM, observability, and distributed systems. Builds automation, diagnostics, runbooks, and scalable operational improvements while leading incident response and mentoring Customer Reliability Engineers. Partners with escalation management, account teams, engineering, and customers to improve resolution times, reliability, documentation, and technical enablement. Participates in on-call rotations and communicates complex issues to technical and executive audiences.

Build and operate the platform that schedules, runs, and monitors machine learning training, evaluation, and reinforcement-learning workloads on Kubernetes. Responsibilities include job scheduling, workload networking, runtime isolation, checkpoint storage, automation, infrastructure as code, observability, and production troubleshooting. The role collaborates with AI researchers and ML engineers and includes a compensated 24/7 on-call rotation.