QA Engineer

CodeRound; Hinoba-an; On-site; PHP 600,000 - 1,200,000; Full time

Job summary

CodeRound is seeking a dedicated Automation Engineer to own end-to-end test automation across UI, API, and ML-driven workflows. You will design and maintain frameworks, ensure zero regression, and enable fast release cycles for a complex AI-powered supply-chain SaaS platform.

You will collaborate with product, backend, frontend, and ML teams, implementing tests in CI/CD pipelines and validating deployments in Kubernetes environments. Remote options may apply depending on project needs.

Qualifications

• Experience building automation across UI, API, and data pipelines.
• Ability to design robust test frameworks from scratch.
• Experience with AI-powered QA tools is a plus.
• Familiarity with containerized deployments and cloud environments.

Responsibilities

• Design, build, and maintain automation suites across UI, API, backend services, and LLM workflows.
• Create robust frameworks from scratch using any modern automation stack.
• Automate test coverage across microservices, workflows, and high-throughput pipelines.
• Define and implement full-stack test strategy covering functional, regression, sanity, smoke, performance, and integration testing.
• Write automation for highly dynamic datasets, multi-agent flows, async pipelines, and K8s-based deployments.
• Leverage AI-based QA tools to accelerate test creation and coverage.
• Set up validation pipelines for agentic flows using both rules + AI models.
• Integrate automation into CI/CD (GitHub Actions / Argo / Jenkins).
• Work closely with DevOps to run tests inside EKS, staging, and preview environments.
• Debug issues across distributed systems, logs, and Docker-based environments.
• Work closely with product, backend, frontend, and ML teams and be the “automation guardrail” for all releases.

Skills

Test automation

CI/CD

Debugging

Tools

Selenium

Playwright

Cypress

Appium

PyTest

JUnit

Job description

Client: It is an AI-powered supply-chain SaaS platform focused on demand forecasting, inventory planning, purchase/replenishment automation, distribution planning, and inventory visibility. It uses AI/ML to help D2C, FMCG and other brands reduce stock-outs and overstocking.

Requirements:

The company is building the world’s most advanced AI-driven supply-chain operating system forecasting, procurement, distribution, planning, and intelligent automation at massive scale. Our platform handles billions of data points, multi-agent LLM workflows, real-time orchestration, and mission-critical decision automation for enterprise brands.You will be the owner of test automation across multiple product modules (Forecast Engine, Procurement Agent, Distribution Engine, Workflow Builder, Vendor Portal, etc.). Your role ensures bulletproof releases, fast feedback cycles, zero regression, and deep automation coverage for both traditional backend systems and LLM-powered modules. If you’ve built automation using Selenium, Playwright, Cypress, Appium, PyTest, JUnit, etc. — great. If you’ve used new-age AI-powered automation tools (e.g., Cerbos, Waldo, QA Wolf, Testim.io, Mabl, etc.) — big plus.

Responsibilities:

• Design, build, and maintain automation suites across UI, API, backend services, and LLM workflows.
• Create robust frameworks from scratch using any modern automation stack.
• Automate test coverage across microservices, workflows, and high-throughput pipelines.
• Define and implement full-stack test strategy covering functional, regression, sanity, smoke, performance, and integration testing.
• Write automation for highly dynamic datasets, multi-agent flows, async pipelines, and K8s-based deployments.
• Leverage AI-based QA tools to accelerate test creation and coverage.
• Set up validation pipelines for agentic flows using both rules + AI models.
• Integrate automation into CI/CD (GitHub Actions / Argo / Jenkins).
• Work closely with DevOps to run tests inside EKS, staging, and preview environments.
• Debug issues across distributed systems, logs, and Docker-based environments.
• Work closely with product, backend, frontend, and ML teams and be the “automation guardrail” for all releases.