Top Remote Linux Jobs in San Diego, CA

Designs and deploys secure, scalable solutions for military and operational customers. Responsibilities include technical discovery, infrastructure validation, network configuration, deployment readiness, security accreditation support, API and data integrations, technical demonstrations, pilot deployments, and translating field experience into reusable implementation patterns. The role partners with Sales, Platform Engineering, SRE, Cybersecurity, Product, and customers, and requires 30–50% travel.

Build and operate GitLab’s Rust-based Knowledge Graph backend supporting SDLC and code indexing, graph queries, MCP endpoints, AI agents, and analytics. Integrate with Rails, ClickHouse, NATS JetStream, and Data Insights systems. Improve reliability, observability, scalability, and operational readiness through testing, metrics, runbooks, alerts, and on-call participation. Collaborate asynchronously across product, data, infrastructure, security, and AI teams while contributing to system design and occasional Ruby or frontend work.

Build and operate a scalable data platform supporting warehousing, orchestration, business intelligence, governance, and agentic workflows. Develop Python services, Terraform infrastructure, and developer tools for petabyte-scale data. Partner with data practitioners and product teams, establish security and reliability patterns, set technical direction, improve engineering standards, and mentor engineers.

Build and operate Dragos’s web application, GraphQL and gRPC APIs, and client SDKs. Develop React and TypeScript features, design versioned API contracts, maintain Python, TypeScript, and Go SDKs, and collaborate with Product, Design, and backend engineering. Improve performance, accessibility, observability, security, testing, and code quality while supporting security data at scale.

Design, build, and operate hybrid/multi-cloud and on-prem platform infrastructure. Lead cross-team initiatives, automate via IaC/CI-CD, apply AI tools for operations, implement observability and security best practices, provide tier-3 support and on-call coverage, and create reusable platform patterns and self-service capabilities for data and analytics workloads.

A 12-week unpaid fellowship providing hands-on training in Palantir Foundry and AIP. Participants attend live virtual instruction, complete technical projects, engage with Palantir engineers and leadership, and earn a professional certification. The program seeks builders with technical experience in software, data, automation, process improvement, prototyping, or related fields. Exceptional performers may interview for roles at Palantir or partner companies.

Serve as the technical bridge between Engineering, Product Management, and field teams. Translate cloud requirements into product requirements, validate enterprise architectures and workflows, and conduct hands-on feature and integration testing. Enable post-sale implementations through documentation, solution briefs, demos, and technical guides. Advise customers and partners on cloud architecture and integrations while supporting sales engineering and professional services teams.

Design and implement C++ features for MongoDB’s replication infrastructure, improving availability, recovery, consistency, performance, and fault tolerance. Diagnose distributed-systems issues, develop comprehensive tests, collaborate across engineering teams, participate in design and code reviews, and mentor junior engineers. The role involves owning technical work from investigation through delivery and contributing to major MongoDB releases.

Build and evolve scalable, performant software services supporting production AI systems. Responsibilities include writing quality code, designing cloud-neutral microservices, optimizing and deploying AI models, contributing to architecture and design discussions, leading the software development lifecycle, mentoring engineers, and collaborating cross-functionally. The role requires expertise in Go or another major programming language, Python, DevOps technologies, cloud architecture, databases, and scalable service development.

Improve Radar’s geocoding and autocomplete systems at massive scale by enhancing query understanding, retrieval, ranking, relevance, and location-data quality. Build automated data pipelines, integrate messy global sources, and apply ML or LLMs where useful. Work across Scala and Python data pipelines, Rust search and serving systems, and customer-facing product improvements while participating in on-call support.