Top Remote Infrastructure Engineer Jobs in Austin, TX

Designs, implements, and maintains Azure cloud infrastructure, Azure DevOps pipelines, and Terraform-based Infrastructure as Code. Serves as a technical expert across infrastructure and application teams, ensures cloud solutions meet security and vendor best practices, develops technology roadmaps, performs root cause analysis, and documents managed services. The role also supports Microsoft cloud integrations, lifecycle planning, and communication of technical concepts to nontechnical stakeholders.

Designs, deploys, and manages secure, scalable cloud infrastructure across AWS, Azure, or hybrid environments. Responsibilities include cloud networking, API gateways, IAM, Kubernetes and EKS administration, infrastructure automation, monitoring, disaster recovery, security, compliance, incident troubleshooting, and performance optimization. The role collaborates with application, platform, security, and DevOps teams while maintaining infrastructure standards and documentation.

Design, build, operate, and improve cloud infrastructure, deployment systems, observability, developer tooling, and distributed systems. Own infrastructure products end to end, manage systems with Terraform, support scalable AWS and Kubernetes environments, operate Redis/ElastiCache, participate in incident response, improve reliability and performance, and mentor engineers while collaborating across teams.

Own infrastructure, deployment, operational tooling, observability, deploy safety, and incident response for latency-sensitive institutional trading systems across cloud and colocated environments. Improve reliability, performance, and developer velocity; reduce single points of failure; establish operational standards and automation; partner with engineering, product, markets, and SRE; and mentor engineers in a 24/7 production environment.

Design, build, and run secure production infrastructure across cloud-native and air-gapped deployments. Own end-to-end platform outcomes, harden the artifact pipeline for signed releases, embed with teams to advise on security and deployment best practices, and partner with GRC on STIGs, CVE remediation, and audit readiness for classified environments.

Build, operate, and secure cloud-native and edge infrastructure including Kubernetes, artifact pipelines, application streaming, and air-gapped appliances. Partner with product, GRC, and mission owners to design, deploy, and harden systems, remediate vulnerabilities, support audits (IL5/IL6/JWICS), and ensure trusted artifact delivery across environments.

Design, build, and operate distributed storage and file-system platforms for cloud-scale AI training and inference. Architect storage and caching for Kubernetes and GPU workloads, improve performance, reliability, observability, and resiliency, diagnose cross-layer production issues, and lead architecture reviews. Partner across infrastructure, networking, operating systems, and AI platform teams while mentoring engineers and shaping long-term storage strategy.

Own and improve Glydways’ Bazel monorepo infrastructure across C++, Python, and Go. Responsibilities include implementing remote caching and remote build execution, optimizing build and test performance, maintaining toolchains and dependencies, supporting embedded cross-compilation, improving CI/CD workflows with AWS and Buildkite, developing developer automation, monitoring build health, and participating in on-call support.

Develop and operate Akamai’s Linux-based cloud infrastructure, including bare-metal and virtual machine platforms, kernels, operating systems, and KVM/QEMU virtualization. Build software, automation, observability, and infrastructure enhancements at scale; troubleshoot complex distributed-system issues; collaborate across engineering and operations; mentor team members; and participate in on-call service restoration.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

Leads the design, automation, operation, and scaling of infrastructure across on-premises data centers, GCP, and AWS. Responsibilities include infrastructure as code, configuration management, networking, load balancing, DNS, monitoring, observability, distributed systems administration, documentation, technical direction, project leadership, and mentoring. The role requires deep Linux, hardware, networking, cloud, storage, backup, and Python automation expertise.

Design, build, and maintain infrastructure software for large-scale AI training and inference. Improve efficiency, resiliency, availability, observability, and reliability across distributed AI systems. Develop APIs and tools, analyze failures from application through hardware levels, define reliability metrics, and support NVIDIA AI platforms. The role requires expertise in distributed systems, monitoring, debugging, software engineering practices, and AI infrastructure, with preferred experience in large clusters, RDMA stacks, telemetry, and deep learning frameworks.

Design, build, and operate secure cloud-native and edge infrastructure for classified and commercial environments. Own end-to-end platform outcomes, harden artifact pipelines for signed builds across cloud and air-gapped deployments, embed with product teams to advise on secure deployments, and support compliance/audit activities (STIGs, CVE remediation) to enable operation in IL5/IL6/JWICS environments.

Build and operate foundational developer infrastructure across CI, build systems, deployment orchestration, and test platforms. Improve build speed, deployment safety, test reliability, observability, and engineering productivity at scale. Own services from architecture through production, including SLOs and on-call operations. Lead cross-functional technical projects, partner with engineering teams, mentor engineers, and shape platform strategy.

Evaluate properties for modular GPU-compute deployments by assessing electrical capacity, equipment, fiber, access, and permitting. Lead utility coordination, electrical design, contractor bids, construction, testing, commissioning, and turnover. Develop site-readiness standards and investment memos while coordinating utilities, consultants, vendors, network providers, and property teams. Maintain as-builts, capacity records, commissioning documentation, and vendor data. This remote role requires frequent travel throughout the United States.

Design, build, and operate foundational developer infrastructure across CI, build systems, deployment orchestration, and test platforms. Improve build speed, deployment safety, and test reliability while owning services end to end, including SLOs, observability, and on-call responsibilities. Partner with engineering teams to address platform pain points and lead cross-cutting technical projects through production.

Build and maintain scalable AWS infrastructure using Terraform and AWS CDK. Design highly available cloud environments, automate operational workflows with TypeScript, implement policy-as-code guardrails, optimize cloud costs, and lead disaster recovery planning and testing. The role also involves CI/CD, Kubernetes, networking, identity platforms, cross-team consensus building, project ownership, communication, and mentoring junior engineers.

Build and operate scalable ML infrastructure for data preparation, model training, evaluation, deployment, monitoring, and rollback. Develop AWS and Kubernetes platforms, reproducible pipelines, dataset and model versioning, observability, testing, security controls, and self-service tooling. Partner with autonomy, software, data, simulation, and security teams to support cloud-to-edge ML workflows and reliable production deployments.

Build and operate reliable, scalable production infrastructure for GitLab’s user-facing services. Responsibilities include developing infrastructure automation and tooling, managing Kubernetes deployments, maintaining infrastructure as code, supporting CI/CD and GitOps, participating in on-call and incident response, improving observability and SLOs, troubleshooting production systems, and documenting operational practices. The role spans Intermediate through Senior Staff levels and requires strong software engineering, cloud, reliability, and asynchronous collaboration skills.

Own product and infrastructure security across fintech products and cloud environments. Lead threat modeling, architecture reviews, secure code reviews, vulnerability management, bug bounty operations, CI/CD security scanning, IAM and secrets management, and security standards. Partner directly with engineering leadership to identify and remediate critical vulnerabilities across backend services, APIs, frontends, Solana programs, and infrastructure.

Leads Wasabi’s AI infrastructure, data factory, and developer partnerships strategy. Hunts and originates new relationships, develops joint go-to-market and co-selling motions, structures revenue-generating deals, and manages executive partner relationships. The role collaborates with Business Development, Sales, Marketing, and Product, builds the developer ecosystem, tracks pipeline and revenue performance, and represents Wasabi at industry events. Candidates need deep AI infrastructure and storage expertise, an established industry network, and a proven record of closing strategic partnerships.

Design and build Kubernetes-based LLM serving infrastructure, including GPU scheduling, scaling, model lifecycle management, Helm packaging, enterprise and offline deployments, API integrations, and production observability. Develop across a multi-service Go codebase, contribute design documentation and reviews, and help guide engineering direction. The role requires strong Kubernetes, distributed systems, CI/CD, and infrastructure-as-code expertise, with GPU, inference, or adjacent systems experience.

Leads infrastructure and data platform strategy across multiple technology teams. Oversees technical architecture, modernization, cost optimization, high-priority incident escalation, vendor collaboration, proof-of-concept development, and technology roadmaps. Provides technical leadership, mentoring, coaching, and best-practice evangelization while driving interoperability, innovation, and consistent platform adoption across the portfolio.

Design, build, and maintain scalable AWS and Azure infrastructure using Infrastructure-as-Code. Develop automation, deployment pipelines, and production release processes. Contribute code to cloud services, manage networking and IAM, ensure availability and security, and respond to incidents while collaborating on observability and security practices.

Lead design and delivery of agentic AI systems and LLMOps on AWS to generate, validate, and deploy infrastructure-as-code (Terraform). Build multi-agent applications, RAG pipelines, and AIOps for cloud operations; integrate AI into CI/CD and ITSM. Set technical direction, establish guardrails/policy-as-code, curate reusable Terraform modules, and mentor engineering teams.