Top Entry Level Linux Jobs in San Diego, CA

Supports audio, video, and lighting production systems for worship services, events, weddings, and funerals across multiple campuses. Responsibilities include equipment setup, troubleshooting, repair, maintenance, stage design support, technical operation, training, and project assistance. The role requires schedule flexibility, including Christmas and Easter availability, strong teamwork, independent judgment, reliability, and commitment to the church’s mission and Christian values.

Build production AI-agent integrations embedded within enterprise engineering teams. Write code and scripts connecting Harness AI Agents to pipelines, repositories, ITSM tools, security systems, and infrastructure. Collaborate directly with customer engineers, prototype and deploy incrementally, create reusable integration patterns, and support customer transition to independent operation. The role requires strong CI/CD and infrastructure-as-code knowledge, integration experience, stakeholder communication, comfort with ambiguity, and frequent travel to customer sites.

Build and maintain a large case law dataset through document metadata pipelines, web scraper reliability systems, citation-resolution utilities, APIs, and evaluation benchmarks. The role requires backend technical generalism, data pipeline expertise, and basic-to-intermediate infrastructure and DevOps skills. Python and SQL are core, while ML and AI experience is beneficial. This is an in-person position in SoHo, New York City.

Own the workflow engine powering customer runs, including scheduling, queues, retries, batching, idempotency, provider integrations, observability, and cost controls. Scale Postgres and Redis while improving reliability across high-volume data workflows. Work autonomously, use coding agents extensively, and make technical decisions for an early-stage platform.

Build and operate scalable cloud and on-prem infrastructure, lead Kubernetes migration, improve Kafka-to-Quickwit ingestion and search performance, automate provisioning with Terraform and Helm, establish observability and reliability targets, and manage incidents, upgrades, backups, and recovery.

Talent community opportunity for future technical roles at RapidSOS. Potential responsibilities include developing and supporting life-saving technology, collaborating with Product on public safety solutions, leading or supporting engineers, owning strategic initiatives, and improving tools and processes. Candidates should be collaborative, self-motivated, adaptable, detail-oriented, eager to learn and leverage AI, and comfortable in a fast-paced startup environment.

Provides technical leadership to design, analyze, and improve manufacturing processes, systems, workflows, and layouts. Develops labor standards, capacity models, cost estimates, and standard work documentation. Applies lean manufacturing and problem-solving methods to improve safety, quality, productivity, throughput, flow, and costs. Troubleshoots process and system issues while collaborating with operations, quality, supply chain, engineering, vendors, and customers to implement improvements.

Work alongside developers on real projects: write and run unit and integration tests, implement minor code changes, fix bugs, and learn software development practices.

Develop and maintain full-stack features for a SaaS platform supporting clinical trial workflows. Responsibilities include Python-based application development, frontend collaboration, architecture, testing, code review, refactoring, reliability, data integrity, and regulatory compliance. The engineer will collaborate with product, design, machine learning, infrastructure, clinical, QA, and regulatory teams while contributing to a distributed engineering organization.

Build and operate platform infrastructure across PostgreSQL, GCP, data systems, developer tooling, security foundations, and agentic systems. Own infrastructure projects from discovery through production, including migrations, observability, rollback planning, reliability, scalability, and internal customer feedback. Develop shared frameworks, evaluations, harnesses, sandboxes, and interfaces for cloud-based agent workflows while improving developer velocity and platform quality.