Top Remote Linux Jobs in San Diego, CA

Build, deploy, and operate production software for enterprise logistics customers. The role involves developing core delivery orchestration infrastructure, integrating APIs and platforms, debugging fleet and logistics workflows, taking products from concept through deployment, and collaborating directly with customer engineering, operations, and executive teams. The engineer will also partner with product and AI teams to shape the company’s North American engineering strategy.

Owns platform architecture, standards, data governance, integration patterns, and lifecycle decisions for Blackbaud’s Awareness to Revenue platforms, including Salesforce. Establishes shared technical direction across an Agile Release Train, defines architectural enablers and non-functional requirements, manages technical risk, and mentors engineering teams. The role partners with solution and enterprise architects, supports scaled Agile ceremonies, and ensures secure, reliable, operable platforms through DevSecOps and continuous delivery practices.

Leads end-to-end technical implementations of digital pathology solutions, including environment configuration, integrations, data migrations, testing, go-live stabilization, and troubleshooting across application, infrastructure, networking, storage, identity, and database layers. Develops deployment automation, identifies risks, mentors engineers, improves implementation standards, and collaborates with customers, architects, project managers, Product, Engineering, and Support.

Own end-to-end quality for new features across the operator portal, backend platform, and endpoint agent. Translate requirements into runnable acceptance coverage, build and maintain parallel browser test frameworks, validate APIs and contracts, and integrate suites into CI release gates. Curate automated and AI-generated scenarios, assess test risk, report coverage and failures, and close quality gaps. The role also drives adoption of shared tooling and may involve containerized environments, cloud platforms, virtualization, performance testing, and security product testing.

Build and improve Replicant’s AI-native platform, including site reliability, CI/CD, developer tooling, observability, incident management, cloud infrastructure, and autonomous-agent harnesses. Own production infrastructure reliability at scale, reduce operational toil, improve deployment workflows, participate in on-call rotation, and shape platform engineering patterns. The role uses TypeScript/Node.js, Python, Terraform, Kubernetes, Helm, GCP, and modern monitoring tools.

Build production integrations, data pipelines, spend models, and agentic AI workflows for enterprise procurement customers. Embed with customer teams to normalize messy data, define and measure deployment outcomes, customize reliable workflows, and create customer-specific evaluations. Lead demos, training, security reviews, and pilot implementations while feeding reusable integrations and patterns back into the core platform. Travel to customer sites approximately once or twice monthly.

Leads the software engineering organization responsible for scalable, reliable applications and systems integrating hardware, embedded software, edge computing, cloud infrastructure, and machine learning. Sets technical strategy, develops engineering leaders, drives product delivery, establishes engineering standards, and ensures operational excellence across national-scale deployments. Partners with Product, Deployment, Data Science, and executive leadership to align roadmaps, resolve risks, and build high-performing distributed teams.

Build and improve Replicant’s AI-native platform infrastructure, including site reliability, CI/CD, developer tooling, observability, incident management, and agent harness systems. Own production infrastructure patterns, deployment workflows, and developer self-service across Kubernetes and cloud environments. Participate in on-call and incident response while improving scalability, availability, and operational efficiency for real-time conversational AI traffic.

Provides industrial engineering and project support across warehouse facilities, improving labor productivity, inventory control, service performance, and operating costs. Develops engineered labor standards, incentives, dashboards, scheduling tools, audits, and continuous improvement initiatives. Trains operations teams, evaluates material-handling technologies, manages change, identifies root causes, and drives corrective actions across multiple sites. The role requires extensive travel and collaboration with distribution-center operations.

Provides frontline support for high-availability cloud systems, monitors infrastructure, manages incidents, coordinates outage bridges, documents technical issues, and develops automation and AI agentic workflows. The role partners with development teams to improve detection and resolution, supports AWS technologies, databases, networks, CI/CD tools, and observability platforms. This is a Monday–Thursday overnight shift within a 24/7 command center and includes some holiday coverage.