Top Remote Linux Jobs in San Diego, CA

Develops and executes satellite integration, verification, and validation activities across Flatsat, HWIL, SWIL, and simulator environments. Responsibilities include requirements traceability, test planning, automated TCL scripting for TERMA CCS5, formal test conduction, troubleshooting, data analysis, and test reporting. Supports satellite architecture, CONOPS, interface documentation, and requirements development while coordinating multidisciplinary engineering activities.

Facilitates process hazard analyses using HAZOP, HAZID, What-If, FMEA, Checklist, and LOPA methodologies. Prepares and reviews technical reports, interprets engineering drawings, documents safeguards and recommendations in PHA software, provides process safety guidance, conducts training, and supports clients globally. The role is remote, part-time and flexible, with up to 50% travel, including international travel, and requires strong client communication and process safety expertise.

Architect, deploy, and operate highly available multi-cloud infrastructure across AWS and Azure. Manage Kubernetes, Linux systems, databases, caching platforms, CI/CD pipelines, infrastructure as code, observability, security, incident response, and performance optimization. The role also requires automation with Python and Bash, comprehensive documentation, client collaboration, and participation in a 24/7 on-call rotation.

Designs and delivers complex automated material handling solutions involving conveyors, sortation, pallet handling, AS/RS, robotics, and integrated systems. Responsibilities include customer requirements analysis, system layouts, mechanical drawings, throughput modeling, technical proposals, cost estimates, documentation, supplier coordination, site visits, technical reviews, project support, and mentoring engineers. The role requires deep material handling experience, strong technical writing, knowledge of industrial controls and safety standards, and proficiency with AutoCAD and Microsoft Office.

Analyze and exploit infrared and OPIR sensor data, including SBIRS systems; develop sensor models and advanced processing algorithms in Python and MATLAB; investigate infrared phenomenology; design tests and experiments; troubleshoot data workflows and software logic; and support CONOPS, technical documentation, and technology transition efforts with government, industry, and research partners.

Lead the design and delivery of complex automated material handling systems, including conveyors, sortation, pallet handling, AS/RS, robotics, and integrated technologies. Evaluate customer requirements, develop system layouts, drawings, technical proposals, cost estimates, documentation, and bills of material. Support projects from concept through execution and integration, coordinate with customers, suppliers, and subcontractors, conduct site visits, review technical work, and mentor engineering team members.

Design and maintain scalable services, APIs, distributed systems, and data pipelines for AI training data infrastructure. Own systems through design, implementation, testing, deployment, and monitoring. Lead architectural decisions, improve reliability and scalability, mentor engineers, and collaborate with AI/ML, product, and data operations teams. Contribute to CI/CD, containerization, DevOps, and cloud deployment practices.

Build and operate low-latency, reliable platform infrastructure for AI model evaluation, including APIs, AI gateways, streaming systems, serving layers, observability, authentication, rate limiting, usage metering, and audit logging. Integrate multiple LLM providers, handle failures and response normalization, support enterprise requirements, and contribute across backend evaluation and leaderboard platforms. This hands-on role requires strong Go expertise and experience with distributed systems or developer-facing infrastructure.

Leads the Data Platform and Infrastructure team, owning strategy, architecture, execution, and organizational development. Responsibilities include managing and mentoring engineers, guiding data ingestion and platform design, establishing APIs, SLAs, governance, security, monitoring, disaster recovery, and cost optimization. The role partners with Product, Data, Finance, Security, and Analytics teams to enable reporting, experimentation, machine learning, and data products while scaling reliable infrastructure and developing future technical leaders.

Staff Software Engineer leading architecture, hands-on development, and delivery of reliable frontend, backend, API, data, and production systems across multiple teams. The role drives multi-quarter initiatives, AI-enabled engineering practices, system scalability, security, observability, incident response, technical standards, mentorship, and alignment between technical investments and product outcomes.