Top Entry Level Linux Jobs in San Diego, CA

Architect and support multi-cloud infrastructure, primarily on GCP and Vertex AI with Azure integration. Design enterprise AI platforms, including generative AI, RAG, fine-tuning, and agentic workflows. Establish infrastructure-as-code, security, IAM, governance, MLOps, migration, monitoring, and FinOps standards. Document architectures, review deployments, collaborate across engineering and data science teams, and mentor staff on cloud best practices.

Leads test automation strategy, quality standards, metrics, and test coverage improvements. Develops automated testing for cloud environments, coordinates test planning and execution, and removes delivery blockers. Requires expertise in cloud services, system and network administration, infrastructure automation, programming, continuous integration, and application integration protocols.

Build and operate production cloud infrastructure for an agentic security platform. Responsibilities include Kubernetes, infrastructure as code, CI/CD, databases, observability, security hardening, workflow orchestration, internal tooling, and production debugging. The role partners with engineering teams to improve deployment safety, system reliability, operational security, and developer productivity.

Designs and supports customer-specific powder coating systems, including layouts, detailed drawings, specifications, bills of materials, manuals, and compliance analysis. Collaborates with sales, operations, vendors, service, and customers throughout project development and installation. Troubleshoots issues, conducts design and safety reviews, supports demonstrations and training, and provides onsite assistance. Uses AutoCAD, Microsoft Office, and PTC Creo while applying mechanical, electrical, pneumatic, and industry-standard compliance knowledge.

Lead architecture, design, integration, testing, and flight validation of critical autonomous aircraft structures and hardware. Own systems from concept through production, perform sizing, loads analysis, and trade studies, resolve interfaces across structures, avionics, propulsion, and payload systems, and partner with manufacturing on scalable designs. Participate in aircraft builds and flight-test campaigns while mentoring engineers and establishing technical standards.

Troubleshoot complex Linux, NVIDIA GPU, CUDA, Docker, virtualization, networking, hardware, and AI workload issues. Own escalated support tickets, assist clients and infrastructure suppliers, identify root causes, and collaborate with engineering teams. Build Python and Bash diagnostic tooling, create runbooks, improve monitoring and troubleshooting processes, and support supplier onboarding and machine management. The role is fully or mostly on-site in Los Angeles, with schedules covering Monday-Friday or Sunday-Thursday.

The job description provides no role-specific responsibilities or qualifications beyond the Vice President Technical title and the employer’s equal opportunity statement.

Develop and maintain large-scale Java applications across the full software lifecycle, including design, development, testing, deployment, and maintenance. Build front-end applications using Salesforce, JavaScript, TypeScript, HTML, CSS, and jQuery, with Java, REST, JDBC, and Oracle on the back end. Apply DevOps and CI/CD practices, AWS services, Agile methodologies, and software development best practices while translating requirements into maintainable solutions and improving team performance.

IEM is building a talent community for future opportunities at its new San Antonio site. Interested individuals can share their experience and career interests to receive updates about potential roles. Joining the community does not constitute a job application or guarantee consideration. IEM develops electrical distribution solutions and offers opportunities for engineers, makers, and problem-solvers across its operations.

Own infrastructure for deploying and operating customer-specific AI models. Responsibilities include production deployments, customer data isolation, security hardening, AWS cloud and GPU resource management, cost optimization, monitoring, logging, ETL pipelines, model versioning, ML lifecycle management, and automated testing. The role requires Python, cloud computing, CI/CD, infrastructure-as-code, security fundamentals, ML workflow familiarity, and a strong computer science background.