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!

NVIDIA is looking for a Software QA Engineer with a strong background in Networking and Automation to join our InfiniBand (IB) and NVLINK (NVL) Switch QA team. Our team is responsible for qualifying software stack for NVIDIA’s IB Switch, Router, Gateway and NVLINK systems, delivering world-class networking solutions. You will work at the heart of cutting-edge technology, validating software management features, designing topologies, developing automated test suites, and collaborating with engineering and product teams to ensure delivery of robust and scalable systems. What you’ll be doing: • Design, develop, and execute manual and automated tests as part of software stack releases. • Define, build, and manage testbed topologies for functional, regression, and performance validation. • Analyze architectural designs and feature requirements for new networking capabilities. • Debug failures, identify root causes, and verify fixes delivered by development teams. • Schedule test runs, track testing progress, and generate test status reports with detailed defect documentation. • Write and maintain automation tests across multiple frameworks (Python, Perl), enhancing test efficiency and scalability. • Collaborate with cross-functional global teams including R&D, product marketing, and system verification. What we need to see: • B.Sc. in Computer Science, Information Systems, Electrical Engineering, or related technical field. • 1-3 years of hands-on experience in the field of QA testing • Strong understanding of software testing methodologies, test planning, and bug lifecycle. • Hands-on experience in automation scripting (Python, Perl, or Shell) on Unix/Linux platforms. • Familiarity with networking concepts, protocols, and devices (e.g., switches, NICs). • Strong analytical and debugging skills with an eye for detail. • Clear verbal, proficient written and spoken English Ways to stand out from the crowd: • Experience in Python automation and working with source control tools (Git, Gerrit), Solid knowledge of Linux and kernel internals. • Hands-on experience with virtualized and mixed computing environments (KVM, VMware, Linux/Windows). • Experience using Generative AI platforms / LLMs such as Gemini, Claude, Copilot, etc. to develop tools powered by artificial intelligence. • In-depth understanding of TCP/IP, routing protocols, LAN switching, and data center topologies. • Exposure to QA methodologies, release management, and end-to-end test lifecycle. Familiarity with NVIDIA technologies such as Infiniband, NVLINK, GPUs is a strong advantage.

What if your Python automation caught a critical ASIC bug before the physical silicon was even manufactured? At NVIDIA, our simulation platforms make that happen every release cycle! We are the System Ethernet QA Team at NVIDIA's R&D center, responsible for the testing and qualification of virtual networking silicon (SimX) and software—from L2 forwarding and L3 routing to overlays, QoS, and security. With SimX, developers and QA engineers get hardware-free, early access to the ASIC for better debugging. We are looking for a Senior QA Software Engineer who combines network protocol expertise with strong Python automation skills. Does debugging a BGP EVPN route leak excite you as much as refactoring a test framework? Then we should talk! What you'll be doing: We don't just complete checklists; we collaborate closely with R&D to lead the quality of new features from design to deployment. In this role, we: • Review architectural designs and requirements for new features introduced to the product • Drive the design, development, and execution of tests across functional, performance, and security scopes as part of SW GA and update releases • Develop Python automation suites built on clean OOP principles • Chase down defects and validate fixes until we fully resolve the root cause • Leverage the SimX platform to validate code and debug the ASIC long before hardware arrives What We Need to See: • Combined network engineering depth with thorough software habits • 5+ years of hands-on QA or networking experience, backed by CCNP-equivalent protocol knowledge: L2 (VLAN, STP), L3 (BGP, OSPF), EVPN, VXLAN, and advanced features like PFC, ECN, RoCE, and QoS • Production-quality Python engineering—specifically, strong OOP design and hands-on experience with Pytest • Deep Linux proficiency (at an LPIC-1 or LPIC-2 level) to navigate system internals, analyze logs, and debug effectively • Clear verbal and written communication, with professional proficiency in written and spoken English • B.Sc. or or B.A. or equivalent experience in Computer Science, Electrical Engineering, or a similar background Ways to stand out from the crowd: • Experience with Docker and traffic generation tools (Ixia, TRex, Scapy) • Hands-on experience integrating tests into CI/CD pipelines (Jenkins, GitLab CI) • Working knowledge of virtualization platforms (KVM, VMware)

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you. So, what’s the role all about? We are looking for a visionary engineering leader to architect and lead our quality engineering discipline into the AI era. You will own automation infrastructure, performance engineering, and all AI-driven quality initiatives - building and mentoring high-performing teams of engineers and architects who set the standard for how modern software is validated at scale. This is not a maintenance role. You will disrupt legacy testing paradigms, champion agentic test generation, and embed AI-quality thinking into every stage of the SDLC — from the first commit to production monitoring. You will be the organizational bridge between engineering velocity and product reliability. How will you make an impact? AI Quality Strategy • Define and lead all AI-augmented quality initiatives across the organization • Deploy LLM-powered test generation, triage, and root-cause analysis tooling • Build frameworks for validating AI/ML model outputs and non-deterministic behaviors • Evaluate and integrate emerging AI quality toolchains (GitHub Copilot, Claude, agents) • Champion responsible AI testing practices, coverage standards, and governance models Automation Engineering • Own the full automation strategy across UI, API, and integration layers • Architect scalable, maintainable test frameworks • Drive shift-left testing embedded in CI/CD pipelines (Jenkins, GitHub Actions) • Establish coverage KPIs, flakiness SLAs, and automation ROI metrics • Lead adoption of self-healing and AI-assisted test maintenance Performance Engineering • Lead performance and load testing strategy at enterprise scale • Define SLOs/SLAs and partner with SRE on reliability thresholds • Design continuous performance validation integrated into delivery pipelines • Drive root-cause analysis for regressions, bottlenecks, and latency spikes • Oversee toolchain including k6, JMeter, Gatling, and APM integrations People & Org Leadership • Lead and grow teams of automation engineers, performance engineers, and architects • Set technical direction, OKRs, and career ladders for the quality engineering org • Hire senior ICs and architect-level talent; build succession depth • Foster a culture of ownership, engineering craft, and continuous learning • Partner cross-functionally with Product, DevOps, and R&D leadership Have you got what it takes? • 12+ years in software engineering or QA, with 5+ years in engineering leadership at the Director level or senior Staff+ with direct reports • Deep hands-on background in test automation architecture — you've built frameworks from scratch, not just inherited them • Proven track record leading performance engineering at scale (10,000+ concurrent users, distributed systems, cloud-native environments) • Experience shipping or operating AI/ML systems and understanding the unique quality challenges they introduce • Prior success managing multi-team orgs with both IC engineers and architects (10–40+ total headcount) • Enterprise software domain experience strongly preferred (SaaS, CCaaS, fintech, or similar high-uptime/regulated environments) AI & Technical Acumen • Working knowledge of LLM capabilities and limitations relevant to software testing (prompt engineering, RAG, agentic workflows) • Experience evaluating or integrating AI coding assistants (GitHub Copilot, Claude, Cursor, or equivalents) in engineering workflows • Comfort with statistical testing concepts: model drift detection, data validation, behavioral testing for non-deterministic outputs • Proficient in at least one scripting/programming language (Python, TypeScript, Java) and modern CI/CD tooling • Familiarity with observability and APM tools (Datadog, Grafana, Dynatrace, New Relic) Leadership • Exceptional communicator — able to translate deep technical concepts into executive-level strategy and roadmaps • Strong organizational influencer who shapes culture and engineering standards beyond your direct org • Data-driven decision maker: you measure quality outcomes, not just activity • Bias for hiring and developing senior talent; you build teams that outlast you • Comfortable operating in ambiguity and driving clarity in fast-moving environments What’s in it for you? Join an ever-growing, market disrupting, global company where the teams – comprised of the best of the best – work in a fast-paced, collaborative, and creative environment! As the market leader, every day at NICE is a chance to learn and grow, and there are endless internal career opportunities across multiple roles, disciplines, domains, and locations. If you are passionate, innovative, and excited to constantly raise the bar, you may just be our next NiCEr! Enjoy NiCE-FLEX! At NiCE, we work according to the NiCE-FLEX hybrid model, which enables maximum flexibility: 2 days working from the office and 3 days of remote work, each week. Naturally, office days focus on face-to-face meetings, where teamwork and collaborative thinking generate innovation, new ideas, and a vibrant, interactive atmosphere. Requisition ID: 10834 Reporting into: Senior Director, Engineering, CX Role Type: People Manager #LI-Hybrid About NiCE NICE Ltd. (NASDAQ: NICE) software products are used by 25,000+ global businesses, including 85 of the Fortune 100 corporations, to deliver extraordinary customer experiences, fight financial crime and ensure public safety. Every day, NiCE software manages more than 120 million customer interactions and monitors 3+ billion financial transactions. Known as an innovation powerhouse that excels in AI, cloud and digital, NiCE is consistently recognized as the market leader in its domains, with over 8,500 employees across 30+ countries. NiCE is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, age, sex, marital status, ancestry, neurotype, physical or mental disability, veteran status, gender identity, sexual orientation or any other category protected by law.