AI QA Technical Lead: Build AI-Driven Testing Tools

Start.io; Poland; On-site; PLN 180,000 - 270,000; Full time

Job summary

Start.io is seeking a hands-on AI QA Technical Lead to steer the QA organization’s evolution with AI. You will design and implement AI-powered tools, agents and workflows used by QA engineers across testing design, automation and data generation.

The role focuses on building scalable solutions, improving quality, and collaborating with QA and engineering teams to turn real-world challenges into practical AI-enabled outcomes.

Qualifications

• 5+ years in Software Quality Engineering, Test Automation or Software Engineering.
• Strong experience with test automation frameworks like Playwright or Cypress.
• Proficient in JavaScript/TypeScript or Python.
• Hands-on experience building AI-powered tools or agents using LLMs.
• Knowledge of prompt engineering, tool calling and API integrations.

Responsibilities

• Design, build and evolve AI-powered QA tools, agents and workflows.
• Identify repetitive QA activities and turn them into scalable AI solutions.
• Create integrations between AI capabilities and testing, engineering systems.
• Define standards and best practices for AI-enabled QA, including prompts and human-in-the-loop processes.
• Build mechanisms to evaluate AI output, measure quality and detect regressions.
• Monitor performance, reliability and cost of AI-powered solutions.
• Act as the technical focal point for AI within QA and foster adoption.
• Collaborate with QA and engineering teams to solve real-world challenges.

Skills

QA fundamentals

Test automation

JavaScript/TypeScript

Python

LLMs

Agent workflows

Problem-solving

Independent initiative

Tools

Playwright

Cypress

GitHub Actions

Jenkins

APIs

Job description

Start.io is seeking a hands-on AI QA Technical Lead to steer the QA organization’s evolution with AI. You will design and implement AI-powered tools, agents and workflows used by QA engineers across testing design, automation and data generation.

The role focuses on building scalable solutions, improving quality, and collaborating with QA and engineering teams to turn real-world challenges into practical AI-enabled outcomes.