DriveNets 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.
What you'll do
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 problems and drive them to resolution
Requirements
Technical Skills
5+ years of hands-on DevOps experience with a strong software development background — prior development experience is a must
B.Sc. in Computer Science or equivalent practical experience
Strong programming skills in Python (or a similar high-level language); ability to write and own production tooling
Proven experience designing and building scalable systems, automation frameworks, and infrastructure as code using Terraform and Helm
Solid understanding of Linux, containers (Docker), and Git-based workflows
Hands-on experience with CI/CD at scale using GitHub Actions or similar — including reusable actions, workflow design, and automation frameworks
Deep experience with hybrid cloud infrastructure (AWS and on-prem), including EKS, ARC, Karpenter, ECR, S3, Direct Connect, VPC endpoints, IAM/OIDC, and Secrets Manager
Experience operating spot and on-demand runner pools for builds, DinD tests, releases, and security scans across multiple AWS regions
Experience with DinD environments (Sysbox, EBS/NVMe, memory limits, overlay storage, MTU/networking) and build caching (BuildKit, sccache, Valkey)
Experience connecting on-prem/self-hosted runners and routing physical device (wbox) test jobs by site and device type
Experience implementing DevSecOps controls and improving platform observability, cost efficiency, and reliability