Top Linux Jobs in Houston, TX

Lead Azure platform projects, manage teams, troubleshoot cloud services, ensure security management, and support clients in a 24x7 environment.

Lead performance practices for large-scale AI systems, enhance datacenter products, and resolve complex performance issues through collaboration and technical expertise.

Design, implement, and operate observability and reliability for cloud platforms. Measure and monitor production systems, reduce toil via automation, drive incident response and on-call practices, and partner with product and platform teams to improve scalability, resiliency, and observability.

Develop, integrate, test, and maintain mission design simulations and software tools (C++, Fortran, Python). Support full software lifecycle, CI/CD, source control, coding standards, documentation, and NASA Class C compliance; collaborate with NASA civil servants and contractors.

Develop, integrate, test, and maintain mission design and simulation software for NASA and commercial spaceflight programs. Implement software enhancements, maintain Class C software per standards, write documentation, support CI/CD and lifecycle activities, enforce coding standards, and collaborate with NASA teams to improve software design and processes.

Administer, monitor, patch, and troubleshoot Linux/UNIX servers across production and non-production environments. Automate tasks with Shell/Bash, collaborate with DevOps, Cloud, Networking, and Security teams, manage virtualization and cloud platforms, support CI/CD and configuration management, participate in incident response and system optimization, and follow security and compliance best practices.

The Principal Engineer will lead the technical ecosystem, ensuring hands-on execution in a high-growth environment, focusing on AI integration and full-stack development.

Design, build, and maintain cloud infrastructure and deployment systems. Create CI/CD pipelines, manage Docker container environments, implement monitoring and alerting, optimize cost and performance, and support blockchain node reliability.

The Principal Software Engineer at Snout will define architectural direction, build features across the stack, and enhance team effectiveness, ensuring quality and performance.

Lead the backend team, setting technical direction for a scalable platform, designing distributed systems in Golang, and mentoring engineers.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

Lead embedded Linux platform enablement for Nabu Casa hardware: maintain and improve Buildroot-based OS support, perform board bring-up, debug platform-level issues, optimise performance and reliability, upstream patches to open-source projects, maintain CI for builds, and document platform architecture and procedures while collaborating with hardware teams and open-source communities.

Lead and evolve secure, automated cloud platforms and CI/CD pipelines using IaC, containers, and Kubernetes. Integrate security tooling, mentor engineers, optimize cloud cost and reliability, and produce technical documentation while supporting Generative AI development workflows.

Own and maintain reliability, performance, scalability, and capacity of massive Ceph storage clusters. Troubleshoot distributed storage issues, build automation (Python/Shell, SaltStack, Ansible), define observability (SLIs/SLOs, PromQL/LogQL, Grafana), and lead lifecycle initiatives like upgrades, expansions, and migrations.

Design, build, and optimize edge data-collection agents for Windows, Linux, and Mac. Collaborate with product, UX, and engineering to deliver backend features, own development lifecycle, create automated tests, support SaaS products, and participate in 24x7 on-call rotations.

Build and lead development of a customer-facing metric store for high-volume telemetry. Design scalable backend services, data models, ingestion pipelines, and query execution paths. Optimize query performance, storage efficiency, and system reliability. Collaborate with Product, Design, and Operations from architecture through production, mentor junior engineers, participate in on-call rotation, and help define testing, deployment, and operational practices.

Partner with customers to deploy collaborative robots: perform onsite hardware/software testing, troubleshoot and repair, conduct readiness assessments, document procedures, replace parts/retrofits, and drive project communication to ensure successful long-term adoption.

Develop and maintain scalable web, mobile, API, and data-platform features as part of an Agile Scrum team. Implement cloud migrations, CI/CD pipelines, test automation, security controls, and production-first practices while troubleshooting production issues and contributing to continuous improvement.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

The Lead Systems HPC Engineer will optimize GPU clusters' performance, troubleshoot issues, integrate new hardware, and collaborate with teams on system-level software development.

Design and build systems for managing bare-metal infrastructure, focusing on automation, hardware provisioning, and software integration with Linux systems.

Design, implement, and maintain private and public cloud infrastructure and data center physical layout. Lead automation, configuration management, virtualization, and OS provisioning across Unix/Linux/Windows and container platforms. Ensure reliability, disaster recovery, capacity planning, security, incident response, and provide operational reporting and technical guidance to stakeholders.

Lead and independently design, implement, and maintain private and public cloud infrastructure and data center systems. Coordinate architecture, capacity planning, automation, virtualization, disaster recovery, security, and cross-team installations. Provide technical leadership, incident/change reporting, and mentorship for complex infrastructure solutions.

As an Applied R&D Engineer, you will develop backend application software in a Kubernetes environment, focusing on streaming APIs, system design, and code quality.

Design and implement high-performance, scalable storage systems and client libraries for AI workloads. Build data loading, checkpointing, caching, POSIX-style and object-store integrations, observability and telemetry, and validate performance with platform, SRE, and AI teams using modern engineering practices.