Top Linux Jobs in San Diego, CA

Build internal software products, automations, workflows, and data-flow improvements that enhance business operations. Translate organizational needs into working tools, drive adoption, advise leadership on engineering practices, and support cross-functional change. Approximately 80% of the role involves hands-on software development, with the remainder focused on internal consulting and strategic guidance.

Staff Backend Engineer responsible for architecting complex backend systems, setting engineering standards, developing data-intensive applications, and scaling GenAI products. The role leads technical roadmaps, cloud infrastructure, testing, observability, and AI coding-tool adoption while mentoring engineers and partnering across engineering, product, and business teams.

Own the design, implementation, and operation of third-party integrations, public APIs, SDKs, and internal connectors. Build resilient, event-driven services using Node.js, TypeScript, PostgreSQL, Kafka, Redis, and Kubernetes. Lead system design, production operations, performance optimization, incident response, refactoring, code reviews, mentoring, and cross-functional technical communication.

Lead AMP's multidisciplinary engineering organization to define and execute technology vision and roadmap. Responsible for scaling teams across hardware, software, AI, and infrastructure; driving product development, quality systems, and reliable deployments; partnering with execs and cross-functional teams on budgets, prioritization, and metrics; recruiting and mentoring leaders; and balancing short-term delivery with long-term investments to create business value.

Lead the architecture and technical direction of Forward Financing’s core fintech platform. Design scalable distributed backend systems, guide cross-team initiatives, establish engineering best practices, resolve incidents, and mentor engineers. The role owns the technical roadmap and architectural vision while partnering across teams to improve reliability, observability, code quality, and delivery. Ruby on Rails expertise is required, along with strong communication, influence, agile development experience, and a broad backend or full-stack perspective.

Build and scale Credal’s secure AI platform as a founding full-stack engineer. Own stability, scalability, security, architecture, and product quality while syncing billions of customer records reliably. Develop across frontend, backend, cloud, and AI/ML systems; collaborate directly with customers and go-to-market teams; mentor engineers; and take end-to-end ownership of complex technical and product outcomes.

Build polished web and mobile interfaces for AI agents, including streaming output, real-time progress, citations, approvals, and data-dense research workflows. Own front-end architecture, performance, accessibility, testing, telemetry, and design systems. Develop supporting APIs, streaming endpoints, agent state and session services, MCP tools, and integrations. Collaborate with applied researchers, infrastructure engineers, designers, and product managers to deliver agentic capabilities end to end.

Build and modernize internal full-stack applications and developer tools that improve software development workflows and productivity. Responsibilities include system design, DevOps, CI/CD enablement, technology integration, observability, secure authentication, modernization of legacy tools, code quality, collaboration, and mentoring.

Leads architectural decisions, web roadmap delivery, and API acquisition efforts. Partners with leadership on engineering roadmaps and technical feasibility, mentors engineers, promotes best practices, and guides scalable application development and project planning. The role requires engineering team management, Ruby on Rails experience, cloud application development, strong communication, and effective mentorship.

Develop and maintain high-performance C++ backend systems for Celonis’s query engine and core mining platform. Responsibilities include designing query optimization, transaction management, and distributed data processing algorithms; resolving scalability bottlenecks; implementing parallel execution and resource management; improving database reliability and performance; mentoring engineers; reviewing code; and delivering production features.