#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.
- 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
Skills Required
- 8+ years of QA experience focused on cloud-native applications and distributed systems or microservices
- CCNP-level networking expertise, including routing, switching, L2/L3, IP, ARP, MAC, VLAN, DHCP, and ICMP
- CCNP certification or equivalent hands-on networking experience
- Strong REST and gRPC testing knowledge
- Proficiency with Python and pytest; ability to write maintainable automated tests
- Working knowledge of Docker and Kubernetes
- In-depth Linux experience
- Experience with CI/CD pipelines
- Knowledge of formal testing methodologies and STP, STD, and STR artifacts
- Hands-on experience with test-management tooling such as TestRail and issue tracking tools such as Jira
- Presentation skills using PowerPoint or equivalent
- Ability to matrix-lead and influence cross-functional teams without direct authority
- BSc in Computer Science, Electrical Engineering, or a related technical field, or equivalent hands-on experience
- Experience with workflow engines such as Temporal or Airflow
- Experience with infrastructure as code using Terraform or Helm
- Experience building or heavily using AI or agentic automation in QA
What We Do
DriveNets is a rapidly growing software company that has created a radical new way for service providers and hyperscalers to build their networking infrastructure. DriveNets Network Cloud and DriveNets Network Cloud-AI are new innovative networking solutions that apply the cloud architectural approach to high-scale networking. They bring together the scalability of standard Ethernet Clos architecture with the high performance and reliability of service provider networking, delivering optimal networking performance, scale and cost structure for service providers and hyperscalers. Founded by Ido Susan and Hillel Kobrinsky, two successful telco entrepreneurs, DriveNets Network Cloud is the leading open disaggregated networking solution based on cloud-native software running over standard white boxes. Over three funding rounds, DriveNets raised $587 million. Its solutions are used by tens of service providers globally and are in proof-of-concept and lab trials at dozens of operators and hyperscalers, consistently ranking #1 in trials for breadth of capabilities and solution quality. AT&T, the largest backbone in the US, deployed DriveNets Network Cloud across its core network, and DriveNets is currently transporting more than 52% of AT&T’s core network traffic. DriveNets is engaged with over 100 Tier-1 operators and cloud-providers on large projects in North America, Asia and Europe.
