We are looking for a seasoned QA / E2E engineer who can hold the entire our company 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.
This position is open to all candidates.