ACO QA E2E Engineer
Core
Design, execute, and validate end-to-end testing scenarios for the AI Cluster Orchestrator (ACO), covering UI/UX, APIs, database workflows, and real infrastructure including switch provisioning, telemetry, and AI cluster performance.
Role type
Senior QA Engineer (AI Networking & Infrastructure)
Builds
The AI Cluster Orchestrator (ACO) used to deploy and run high-scale AI infrastructures for service providers and hyperscalers.
Domain
Networking infrastructure, AI/ML hardware, and high-performance computing (HPC).
Deliverable
production ML models
Required skills
End-to-end testing design, CCNP-level networking (L2/L3, BGP, VLAN/VXLAN/EVPN), AI networking (leaf-spine, RoCEv2, RDMA), GPU cluster management (NCCL, MPI, SLURM/Kubernetes), Linux CLI and scripting, AI agent integration (prompt engineering, MCP servers), regression testing, performance benchmarking analysis.
Preferred skills
QA automation (Python, pytest, Playwright), Kubernetes troubleshooting, Cloud deployments (AWS/Azure/GCP), SQL querying, Network OS familiarity (DNOS, SONiC, Junos), Observability stacks (Prometheus, Grafana, gNMI).
Technologies
Python, pytest, Playwright, Selenium, REST APIs, Kubernetes, SLURM, NetBox, gNMI, OpenConfig, Prometheus, Grafana, Spirent, Ixia, NVIDIA GPUs, AMD GPUs, RDMA, NCCL, MPI, RoCE.
Responsibilities
Design and execute comprehensive E2E testing scenarios for ACO; Validate network connectivity and performance across AI cluster infrastructure (400/800G/1.6T Ethernet, leaf-spine topologies); Execute and analyze AI/HPC benchmarks (RDMA, NCCL, MPI) on GPU/CPU clusters; Troubleshoot defects by collaborating with development teams and reproducing issues; Document test procedures, results, and performance metrics; Use AI agents to accelerate test design, execution, and reporting.
Seniority
Senior, hands-on IC
