QA Engineer jobs in Ra'anana

Description #Hybrid R&D – Raanana DriveNets builds high-performance networking solutions for large-scale AI infrastructure and service-provider networks. DriveNets’ Network Cloud powers production networks at global operators such as AT&T and Comcast, while its AI Fabric solutions optimize the performance and time to first token (TTFT) in multi-vendor AI environments at foundation model labs, NeoClouds, and enterprises. DriveNets combines high-performance networking, end-to-end automation, and full-stack AI cluster optimization to remove network bottlenecks, maximize GPU utilization, accelerate AI cluster deployments, and improve token economics The Role We are looking for a seasoned QA / E2E engineer who can hold the entire DriveNets Application Platform (DAP) in their head — from the UI and REST/gRPC APIs, through workflow-engine orchestration and microservices, down to configuration pushed onto real network elements — and prove with evidence that it works end to end. This is not a single-service testing role. You will own end-to-end validation across the DAP platform and matrix-lead the work: bringing development teams, system architects, product, and other stakeholders into a shared definition of success. You will increasingly do this by directing AI agents rather than only writing tests by hand. Responsibilities • Own end-to-end test strategy and execution across the DAP platform — translate features and epics into complete E2E test plans that trace each requirement/acceptance criterion to a concrete test. • Matrix-lead cross-team work: pull in developers from different teams, system architects, and product; align them on risk, coverage, and what "done" means. • Design and execute test plans for REST/gRPC APIs and workflow-engine functionality, including dynamic task addition, orchestration, and state transitions. • Validate configuration and provisioning flows end to end — from UI/CMS edits and config-template rendering through to the configuration applied on the target network element, confirming on-device before/after state. • Build automated suites for contract validation, regression, and critical-path coverage; design negative and failure-mode tests, not just happy paths. • Identify, reproduce, document, and track defects with self-contained, reproducible bug reports (exact flow, inputs, payloads, logs, on-device evidence) and drive them to verified closure. • Present plans, risks, and results clearly — in slides and live walkthroughs — so engineering and product can decide. • Direct AI agents (e.g. Cursor, Claude, agentic subagents) to author test plans, generate and execute tests, and triage failures — while owning correctness of the output. Requirements • 8+ years in QA, with a focus on cloud-native applications and distributed systems/microservices. • CCNP-level networking is a must, routing and switching depth beyond fundamentals (L2/L3, IP, ARP, MAC, VLAN, DHCP, ICMP) and enough protocol skill to validate real device configuration and tell on-box failures from platform failures. • CCNP certification or equivalent hands-on experience. • Strong understanding of REST and gRPC testing methodologies; proficiency with Python testing frameworks (pytest) and writing maintainable automated tests. • Working knowledge of containerization and orchestration (Docker, Kubernetes), in-depth Linux and experience with CI/CD pipelines. • Command of formal testing methodology and artifacts (STP / STD / STR), with hands-on experience in test-management tooling (e.g. TestRail) and issue tracking (e.g. Jira). • Presentation skills (PowerPoint or equivalent) — able to turn a test plan, a risk, or a failure into a clear slide story for mixed engineering and product audiences. • Ability to matrix-lead: influence without authority, bring peers from different teams to a shared picture, and keep the group driving toward the same outcome. • Nice to have: experience with workflow engines (Temporal, Airflow), infrastructure-as-code (Terraform, Helm), and a track record of building or heavily using AI/agentic automation in a QA context. Education And/or Relevant Experience BSc in Computer Science, Electrical Engineering, or a related technical field; or equivalent hands-on experience. DriveNets is an equal opportunity employer. We do not discriminate based on upon race, religion, color, national origin, sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with disability, or other applicable legally protected characteristics. More About DriveNets Based in Israel with locations in Romania, US, and Japan as well as extended teams, DriveNets operations cover more than 16 countries. With recognition by industry analysts and through numerous industry awards, DriveNets is pushing market momentum, allowing for faster service innovation from the network core to the edge. Visit our website: www.drivenets.com

Description Location: Ra'anana #Hybrid DriveNets is a leader in high-scale disaggregated networking solutions. Founded in 2015, DriveNets modernizes the way service providers, cloud providers and hyperscalers build networks. Supporting the largest network in the world, more than half of AT&T’s backbone traffic is running on DriveNets’ Network Cloud open disaggregated architecture. Raising $587 million in three funding rounds, DriveNets is disrupting the networking market from high-scale architecture to AI platforms, and is bringing onboard the most talented people. We are seeking people that want to make an impact on the world’s leading communication networks and are experienced in networking architecture or AI infrastructure solutions. What You'll Do: • Design, create and execute comprehensive end-to-end testing scenarios for ACO based on detailed requirements and design documents. • Test ACO across its UI/UX, REST APIs, database-backed workflows and the real infrastructure it manages: switch provisioning and upgrades, inventory and topology, telemetry, alerts, configuration compliance, benchmarking and multi-tenancy. • Maintain and ensure functionality across the QA environments: AI fabric topologies (leaf-spine, DNOS and multi-vendor switches), GPU servers, NetBox/SLURM/Kubernetes integrations and the ACO deployments. • Validate network connectivity, configuration and performance across the AI cluster infrastructure: high-speed Ethernet (400/800G/1.6T), GPU nodes, leaf-spine topologies, VLAN/VXLAN, IP addressing, MTU, link status, routing and packet loss. • Verify BGP routing functionality (neighbor establishment, route advertisement, route propagation and convergence) and EVPN/VXLAN-based isolation on data-center fabrics. • Execute and analyze existing AI/HPC benchmarks (RDMA, NCCL/RCCL, MPI, RoCE, training/inference, storage) on GPU and CPU clusters through ACO's benchmarking engine; compare actual performance against established baselines. • Review and understand benchmarking methodologies and test procedures for high-performance networking and collective communication technologies. • Support telemetry collection and validate test data (gNMI/OpenConfig counters, syslog, GPU and NIC metrics) for accuracy, consistency and reliability against device state. • Use performance analysis tools, benchmarking frameworks and diagnostic utilities to execute tests, analyze results and troubleshoot issues. • Execute regression tests to verify that software updates, configuration changes and platform upgrades do not introduce new issues. • Collaborate closely with development teams to investigate failures, reproduce defects with clear evidence, verify fixes and ensure system quality. • Document test procedures, execution results, defects and performance metrics to maintain traceability and reproducibility; prepare clear QA reports highlighting deviations, failures and potential issues. • Use AI agents in your daily work to accelerate test design, execution, evidence collection and reporting, and help grow the team's test automation. Requirements What We're Looking For: • Minimum 3 years of application testing across UI/UX, database-backed data and multi-step workflows in web-based systems, including test design from detailed requirements (STP/STD/STR). • Networking knowledge at CCNP level or higher: L2/L3 switching and routing, BGP, VLAN/VXLAN/EVPN, MTU/MSS, ECMP, and troubleshooting with packet captures and device CLI. • AI networking: data-center fabrics for AI workloads – leaf-spine and rail-optimized Clos designs, RoCEv2/RDMA, lossless Ethernet (PFC/ECN/DCQCN), 400/800G/1.6T optics and link health. • GPU clusters: running, monitoring and optimizing AI workloads and benchmarks (NCCL/RCCL, RDMA, MPI, training and inference) on NVIDIA/AMD GPU servers, with schedulers such as SLURM or Kubernetes. • Strong hands-on experience in Linux environments (CLI, networking stack, services, logs, scripting). • Hands-on experience working with AI agents in daily engineering work: agent skills, rules/instruction (markdown) files, MCP servers and tools, and prompt-driven workflows (e.g., Claude Code, Codex, Cursor). • Agile Experience: hands-on experience in Agile work processes. Advantages: • QA automation experience (Python, pytest, Playwright/Selenium, REST API testing, CI pipelines). • Kubernetes and containers (kubectl, Helm, Lens/OpenLens, Argo CD; monitoring pod status, reading logs, troubleshooting). • Cloud deployments (AWS/Azure/GCP, e.g., EKS). • Databases: SQL querying and data validation (PostgreSQL). • Familiarity with network operating systems (DNOS, SONiC, Arista EOS, Junos), observability stacks (Prometheus/Mimir, Grafana/Perses, gNMI) and traffic generators (Spirent/Ixia). Soft Skills: • Excellent interpersonal and communication skills. • High-level proficiency in English (both written and verbal) and clear technical writing. • Self-starter who learns quickly and adapts easily to new technologies. • Ability to work under tight deadlines and manage multiple priorities. • A strong team player with a collaborative mindset. Why Join Us? • Be part of the team building DriveNets' AI Cluster Orchestrator, used to deploy and run some of the most demanding AI infrastructures. • Work hands-on with state-of-the-art AI infrastructure: 800G/1.6T Ethernet fabrics, NVIDIA and AMD GPU clusters, RoCE and collective communication. • Join an AI-native engineering culture where agents are part of the daily workflow. • Collaborate with brilliant minds in a dynamic and supportive work environment. If you're ready to take the next step in your career and work with a world-class team, apply now!