Project Description Creating of user-friendly interface (HMI) tailored for a kitchen appliance, ensuring seamless interaction between users and the device's functionalities. The Technologies used: Qt, a cross-platform application framework, serves as the backbone for constructing the graphical elements of the interface, offering a wide array of tools and libraries for efficient UI design; QML - a declarative language integrated within the Qt framework, facilitates the creation of visually appealing and dynamic user interfaces with its intuitive syntax and powerful features; Squish - a testing tool ensuring the reliability and performance of the HMI by automating the testing process.Responsibilities Define the performance strategy for mobile and backend, in accordance with the QA Lead and the dev teams.  Model realistic workloads: spike, stress, soak, scalability, and capacity tests reflecting mobile traffic patterns (cold starts, caching behavior, offline/online sync).  Apply baseline tests to enable our dev teams to continuously check for performance flaws during the development lifecycle.  Author and maintain k6 suites, including scenarios/executors, thresholds & checks, parameterization, test data management, secrets handling, results artifacts.  Run k6 tests locally and at scale (k6 Cloud).  Analyze test results via Grafana and discuss mitigation strategies for bottlenecks with the dev teams. 

Define performance smoke and regression gates, baseline drift detection, automated reports & dashboards. You'll collaborate with our dev teams, architects and the QA Lead. 

Tech Stack k6 (OSS/Cloud), k6-operator, xk6 extensions, k6 outputs (JSON/Prometheus).  APM: Grafana, OpenTelemetry 

Backend/Infrastructure: Kubernetes, Redis, DynamoDB, AWS/Azure/GCP.

Necessary requirements  3-5 years experience in performance engineering for distributed systems, APIs and/or mobile-backed services.  Deep k6 expertise across the full lifecycle: Test definition and design, scripted scenarios, data/secrets management, test runs, analysis, and reporting.  Sound experience of workload modeling, concurrency, race conditions, back-pressure, and tail latencies (p95/p98).  Hands-on with APM & tracing and capacity planning.  Comfortable with analyzing databases, caches, queues, and communication through different API layers. 

Ability to read code and consult dev teams with concrete improvements. 

Nice to have  XRay knowledge  Practical knowledge in Chaos Engineering