Top DevOps Jobs in Austin, TX

Build and expand Cloudflare's global datacenter network: coordinate installations, manage hardware and contractors, implement consistent processes, perform Linux administration, use configuration management and scripting, and collaborate with SRE and Network Engineering to improve operations and automation.

Administer and optimize high-volume, highly available PostgreSQL and MongoDB environments across GCP and other cloud services. Responsibilities include implementing database changes through Terraform and GitHub, managing replication, backups, disaster recovery, failover testing, performance tuning, security, monitoring, automation, incident response, on-call support, and maintenance. The role collaborates with engineering teams on schema design, query optimization, BigQuery governance, and database reliability.

Leads teams responsible for Inventory software, Linux platform engineering, and software build and release systems. Sets technical direction, oversees reliability, security, quality, CI/CD, automation, and software delivery. Partners cross-functionally to improve platform integration and engineering processes, mentors employees, manages performance, contributes technically, and participates in an on-call rotation for business-critical systems.

Lead the design and implementation of cloud architecture components and deliver low-latency, highly scalable services. Collaborate with desktop agent and AI teams, drive technical decisions across stakeholders, and improve engineering practices through hiring, design reviews, postmortems, code reviews, and mentorship. Apply AI technologies to improve decision-making, workflows, efficiency, and business outcomes while operating resilient, high-volume Tier-1 cloud systems.

Design, build, and operate a federated GraphQL platform using Apollo Federation. Scale router infrastructure across regions, implement multi-tenant routing and schema governance, develop CI/CD workflows, and support telemetry, billing, and Snowflake integrations. Collaborate with platform, data, and product teams to onboard subgraphs, lead technical designs, and mentor engineers.

Develop and operate software infrastructure supporting Arm CPU design and verification. Build automation for distributed HPC workloads, CI and regression systems, observability, source-control and verification-tool integrations. Diagnose complex issues across software, hardware verification, operating systems, compute, and storage. Improve compute utilization, verification throughput, failure analysis, and engineering workflows while delivering maintainable production-quality software.

Automate and operate production infrastructure across on-premises and cloud environments. Monitor system health, triage incidents, manage SLOs and error budgets, develop infrastructure and policy as code, maintain security and observability pipelines, eliminate operational toil, and implement preventative engineering improvements from incident post-mortems. Participate in on-call operations while strengthening reliability, security, and incident response capabilities.

Owns AWS infrastructure, Kubernetes clusters, Terraform modules, networking, access controls, secrets management, deployment pipelines, reliability, performance, and incident response for a security-sensitive defense technology organization.

Manage and scale hybrid Kubernetes infrastructure across bare metal, virtual machines, and public cloud. Build CI/CD and build systems, implement GitOps delivery and progressive rollouts, and establish backup, disaster recovery, observability, and SLO practices. Debug production issues across the Linux, networking, storage, and Kubernetes stack, automate infrastructure with Terraform, Helm, Ansible, Go, and Python, strengthen platform security, and partner with robotics teams on capacity, architecture, and production readiness.

Build and improve DevOps infrastructure for hardware validation and ASIC/SoC bring-up. The role focuses on reducing manual setup and configuration drift, improving regression predictability, qualifying tools and releases, enabling scalable experimentation and AI-assisted validation, and providing automation and self-service tooling that increases validation engineer productivity.