Principal QA Automation Engineer

About Us

KlearNow.AI is on a mission to futurize global trade. Our patented AI and machine learning platform digitizes and contextualizes unstructured trade documents to unlock real-time shipment visibility, drive smart analytics, and provide critical business intelligence—without the hassle of complex integrations.

We empower supply chains to move faster, work smarter, and make data-driven decisions with confidence. With operations in the U.S., Canada, U.K., Spain, and the Netherlands—and aggressive growth plans underway—we’re scaling a global platform for the future of logistics.

We achieve our goals by assembling a team of the best talents. As we expand, it's crucial to maintain and strengthen our culture, which places a high value on our people and teams. Our collective growth and triumphs are intrinsically linked to the success and well-being of every team member

OUR VISION

To empower people and optimize processes with AI-powered clarity.

YOUR MISSION

We’re building a team of bold thinkers, problem solvers, and storytellers. As part of our high-energy, inclusive workplace, you’ll challenge the status quo of traditional supply chains and help shape a more transparent, intelligent, and efficient world of trade.

Whether you're a product innovator, logistics expert, or marketing storyteller—your work at KlearNow.AI will make a measurable impact.

Why Klearnow.ai

Global Impact: Be part of a platform live in five countries and expanding rapidly.

Fast-Growing SaaS Company: Work in an agile environment with enterprise backing.

Cutting-Edge Tech: AI-powered customs clearance, freight visibility, document automation, and drayage intelligence—all in one.

People-First Culture: We invest in our team’s growth and well-being.

Make Your Mark: Shape the future of trade with your ideas and energy.

Experience

8+ years in Quality Engineering with strong automation leadership

Role Summary

We are looking for a QA Automation Architect with AI experience to design, build, and scale UI and Backend automation frameworks for enterprise-grade applications. This role will own the automation strategy, frameworks, standards, and execution while leading QA engineers to ensure high-quality, production-ready releases. Candidates with strong AI-driven QA experience are highly preferred.

Key Responsibilities

Automation Architecture & Strategy

Define and own end-to-end automation architecture for

UI Automation

Backend / API Automation

• Establish automation standards, best practices, and reusable frameworks
• Implement test pyramid strategy and shift-left testing
• Select tools, libraries, and frameworks for long-term scalability

UI Automation

Design and maintain robust UI automation frameworks using

Selenium / Playwright / Cypress

• Automate complex, dynamic UI workflows
• Handle cross-browser testing and data-driven automation
• Reduce flaky tests and improve execution stability
• Own UI regression coverage for critical business flows

Backend / API Automation

Build and scale API automation frameworks using

REST Assured / Karate / Postman

Validate APIs for

• Functional correctness
• Business rules
• Error handling and edge cases
• Automate end-to-end workflows involving asynchronous processing
• Support event-driven testing (Kafka or similar systems)

CI/CD & DevOps Integration

Integrate automation suites with CI/CD pipelines

Jenkins / GitHub Actions / GitLab CI

Enable automated

• Smoke tests
• Regression suites
• Release go/no-go criteria
• Work closely with DevOps to ensure fast and stable pipelines

AI, LLMs & Modern QA Skills (Highly Preferred)

Hands-on experience with AI tools like Cursor to accelerate automation development, improve code quality, and generate/optimize test scripts.

Working knowledge of LLMs, including

• Prompt engineering
• Using AI to create, refactor, and maintain automated test cases
• Generating test scenarios, edge cases, and data sets using AI
• Ability to incorporate AI-driven testing accelerators into daily QA workflows.
• Self-motivated, proactive, and able to drive adoption of AI-based improvements across the QA team.