About the CompanyDriveNets is a leader in large-scale networking solutions for AI infrastructure and service providers. The company's disaggregated networking architecture transforms the economics of large-scale infrastructures while maximizing performance, utilization, and operational efficiency. Its high-performance AI fabric maximizes GPU utilization and accelerates deployments by optimizing the AI stack end-to-end, resulting in higher tokens-per-second and lower cost-per-token. DriveNets' solutions power production networks for global tier-1 operators like AT&T and Comcast, and scale multi-vendor AI infrastructures at foundation model labs, NeoClouds, and enterprises.Responsibilities- Design, build, and operate the internal engineering platform powering DriveNets' build, test, deployment, and security validation workflows at scale- Write and maintain production-grade Python and shell tooling that drives platform automation — this is a hands-on coding role, not just pipeline configuration- Architect and manage hybrid cloud/on-prem execution infrastructure, including large-scale Kubernetes runner pools across multiple AWS regions- Own and evolve CI/CD pipelines at scale using GitHub Actions, including reusable workflows, ARC-based runner orchestration, and build caching strategies (BuildKit, sccache, Valkey)- Operate and tune DinD environments (Sysbox, EBS/NVMe, overlay storage, MTU/networking) for build, test, and release workloads- Connect and manage self-hosted and on-prem runners, routing physical device (wbox) test jobs by site and device type- Implement DevSecOps controls including least-privilege IAM, OIDC, isolated runner groups, container signing, and automated security scans- Drive platform observability, cost optimization, and reliability improvements across the engineering infrastructure- Collaborate cross-functionally with hundreds of engineers to improve engineering velocity and release confidence- Take end-to-end ownership of complex infrastructure
