Top Remote Linux Jobs in Houston, TX

Implements and supports enterprise AI infrastructure platforms across client environments. Configures Kubernetes, workload schedulers, GPU resource governance, containers, observability, security, and related platform services. Performs discovery, deployment, integration, upgrades, troubleshooting, validation, documentation, and knowledge transfer. Collaborates with cross-functional technical teams, contributes to implementation plans and Statements of Work, manages project deliverables, and provides client-facing consulting support. Travel and occasional extended or weekend work may be required.

Designs, implements, validates, benchmarks, troubleshoots, and supports accelerated compute and high-performance storage infrastructure for enterprise AI workloads. Conducts discovery, migrations, installations, configuration, testing, documentation, and client knowledge transfer. Collaborates with project managers, architects, sales teams, partners, and stakeholders to manage scope, timelines, risks, and deliverables. The role requires client-facing consulting, technical documentation, infrastructure troubleshooting, occasional overtime, and travel to client sites or company locations.

Operate and maintain large Kubernetes clusters across data centers and public clouds. Troubleshoot infrastructure, networking, storage, DNS, and control-plane issues; participate in on-call incident response; perform upgrades and capacity changes; build monitoring dashboards and alerts; automate repetitive work with Go or Python; maintain documentation and use AI tools to improve engineering workflows.

Design, operate, and scale SailPoint’s AWS-based Kubernetes infrastructure and service mesh for a global, mission-critical SaaS platform. Responsibilities include cluster architecture, networking, security, GitOps, CI/CD, observability, capacity planning, incident response, compliance, and platform standards. The role influences engineering teams globally, participates in 24x7 on-call support, leads service mesh strategy, and improves reliability, performance, deployment efficiency, and operational practices.

Develop and operate CrowdStrike’s internal cloud management platform and mission-critical CI/CD pipelines. Build APIs and UIs using Go and TypeScript, improve developer productivity, integrate tooling, maintain cloud-native infrastructure, and support secure, highly available software delivery systems. Collaborate with development, infrastructure, security, and SRE teams, ensure SOC2-aware processes, and participate in on-call operations.

Own and improve Dropbox’s Windows endpoint platform, including provisioning, application delivery, patching, compliance, security configuration, troubleshooting, fleet health, and automation. Build code-managed endpoint operations using Intune, FleetDM, osquery, infrastructure-as-code, and GitOps practices. Lead cross-functional improvements, establish reliable deployment workflows, mentor engineers, review code and designs, and document reusable operational practices.

Own complex software systems and critical workflows end-to-end while ensuring reliability, performance, security, and maintainability. Lead architectural decisions, mentor engineers, manage incident response, improve system health, and communicate effectively with technical and non-technical stakeholders. The role requires extensive Ruby on Rails, AWS or equivalent cloud infrastructure, Linux production operations, frontend development, relational databases, testing, CI/CD, and observability experience.

Build and maintain CrowdStrike’s golden-image platform and automated pipelines across Linux, macOS, and Windows. Develop Python automation for image builds, validation, drift detection, and testing; manage infrastructure as code with Ansible, Packer, and Terraform; integrate Jenkins, GitLab CI, and Artifactory; and support image lifecycle operations. The role includes troubleshooting production issues, security hardening, compliance collaboration, documentation, cross-team partnership, and participation in on-call rotations.

Develop and launch NVIDIA HGX GPU-accelerated server platforms for production. Responsibilities include creating diagnostic tests, debugging hardware, firmware, and software interactions, ensuring design-for-excellence and signal integrity compliance, defining manufacturing test specifications, optimizing assembly lines and production screens, analyzing yield data, and supporting customer quality issues. The role requires strong electrical engineering fundamentals, digital design, timing analysis, statistics, fault analysis, and computer architecture expertise.

Develop and deliver complex software features using Ruby on Rails and React. Responsibilities include system design, requirements clarification, deployments, operational support, performance and security improvements, database optimization, AWS infrastructure troubleshooting, SSO integrations, monitoring, web server administration, compliance implementation, automated testing, and mentoring junior engineers.

Installs, configures, maintains, and troubleshoots PLC-based batching and control systems used in dairy and feedlot operations. Integrates software with scales, pumps, meters, and other equipment; diagnoses electrical, networking, mechanical, and software faults; supports Linux, SQL, and Java systems; trains customers; audits system performance; and provides field and on-call support. The role is remote but requires frequent travel to rural agricultural facilities and work around industrial hazards.

Lead full-stack development for Huntress’s SOC platform, building analyst-facing investigation, triage, remediation, queueing, and customer reporting experiences. Shape architecture, data models, interfaces, security practices, reliability, observability, and testing while mentoring engineers and partnering with Product, UX, and SOC stakeholders. The role emphasizes Ruby on Rails, modern frontend development, cloud infrastructure, relational databases, and technical leadership across complex cybersecurity software products.

Leads a managed services engineering team responsible for AIX, Unix, and Linux service delivery. Oversees customer satisfaction, SLA performance, staffing, workload allocation, process improvement, operational procedures, budgets, vendor relationships, and technical service optimization. Manages customer reviews, support escalations, performance management, hiring, on-call schedules, and continuous service improvement while coordinating strategic and tactical technology plans across internal teams and partners.

Develop and lead production software-defined networking for NVIDIA’s global GPU cloud infrastructure. Design multi-tenant control and data planes using Open vSwitch, OVN, OpenFlow, Kubernetes, C, and Go. Build networking services, plugins, automation, testing, observability, and reliability improvements. Lead architecture and code reviews, mentor engineers, support on-call operations, and resolve complex production incidents through diagnostics and source-level debugging.

Serve as the senior technical contact for OEM Federal deployments of NVIDIA GPU-accelerated platforms. Own customer issues end to end, including troubleshooting, failure analysis, RMA procedures, root-cause investigation, and coordination with OEM support and NVIDIA engineering. Support secure Federal environments such as FedRAMP, IL5/IL6, and air-gapped SCIF facilities while maintaining sanitization and chain-of-custody requirements. Analyze multi-GPU systems, firmware, operating systems, networking, storage, and distributed workloads, with up to 35% travel.

Build and operate software automation for large-scale NVIDIA GPU infrastructure. Responsibilities include bare-metal provisioning, hardware validation, firmware upgrades, repair workflows, cluster lifecycle management, BMC and Redfish tooling, and NVIDIA NVL72 and BlueField DPU operations. Diagnose failures across hardware, Linux, networking, and Kubernetes; support incident response, on-call operations, observability, root-cause analysis, and permanent remediation across cloud and on-premises environments.

Leads engineering enablement for large-scale AI/HPC clusters, managing a support team, training and documentation, request intake and prioritization, specialist debugging coordination, and user community development. Partners across architecture, software, firmware, networking, storage, datacenter operations, performance, and program teams. Uses service metrics and user feedback to improve workflows, self-service guidance, resource allocation, and support quality.

Design, develop, optimize, and debug C++ software for ultra-low-latency WebRTC streaming. Implement real-time transport, security, media, and congestion-control protocols; contribute to standards and protocol solutions; define streaming quality KPIs; and integrate software with platform, connectivity, automotive, and hardware systems.

Leads engineering teams developing platform software for GPU-accelerated applications using Kubernetes, container runtimes, Kata Containers, and Confidential Containers. Responsibilities include enabling GPUs as Kubernetes resources, integrating software across NVIDIA’s technology stack, managing priorities, and delivering secure, reliable distributed systems. The role requires deep systems software expertise, engineering management experience, and hands-on knowledge of containers, Linux, cloud computing, virtualization, and confidential computing technologies.

Design and deploy AI networking platforms in customer data centers. Partner with customers on GPU, compute, storage, and fabric architecture; support infrastructure bring-up; troubleshoot InfiniBand, RoCE, Linux, NIC, and switching issues; conduct technical reviews; build proof-of-concepts; and translate customer requirements into product and engineering feedback. Collaborate with systems engineering, product management, and sales while supporting large-scale AI cluster deployments.

Develop and maintain automated integration and deployment for components in a Kubernetes-based software stack. Manage third-party dependencies, validate compatibility, maintain integration workflows, troubleshoot cross-component issues, and ensure compatibility with NVIDIA hardware. The role requires extensive Linux software development experience, Python proficiency, Kubernetes and container expertise, and collaboration with QA, CI/CD, development teams, and upstream projects.

Lead architecture and roadmap for Azure PostgreSQL systems; design and review scalable, maintainable database engine features (query processing, storage, transaction logging, recovery, versioning, IO, scale-out). Influence coding standards and run code reviews, write proof-of-concept or production code, contribute to open-source PostgreSQL/Linux, and participate in rotational on-call operations.

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

As a Principal Software Engineer, you'll develop software systems for NVIDIA's rack-scale infrastructure, defining software architecture, collaborating across teams, mentoring engineers, and ensuring high-quality technical decisions in complex environments.

Primary point-of-contact for a customer, providing on-site and remote HPC, Ethernet, and AI infrastructure support. Troubleshoot Linux systems, networking protocols, and interoperability; reproduce and resolve complex issues; collaborate with engineering, marketing, and support; document support methodologies and improve processes.