AI Quality Engineer

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

Description

Start.io is a mobile marketing and audience platform. Start.io empowers the mobile app ecosystem and simplifies mobile marketing, audience building, and mobile monetization. Start.io's direct integration with over 500,000 monthly active mobile apps provides access to unprecedented levels of global first-party data, which can be leveraged to understand and predict behaviors, identify new opportunities, and fuel growth.

We are looking for a hands-on AI QA Technical Lead to drive the technical evolution of our QA organization through AI.

Your mission will be to identify opportunities across the QA lifecycle and turn them into practical, scalable AI-powered capabilities that help the entire QA team work faster, smarter and with higher quality.

You will design and build AI-powered tools, agents, workflows and integrations used by QA engineers across the testing lifecycle - from test design and automation to test data generation, debugging and failure investigation.

This is a hands-on technical leadership role with a strong focus on building, experimentation and innovation.

What You'll Do:

• Design, build and evolve AI-powered tools, agents and workflows that improve the efficiency and quality of the QA team.
• Identify repetitive or high-impact QA activities and turn them into scalable AI-enabled solutions.
• Build integrations between AI capabilities and our testing, engineering and internal systems.
• Define technical standards and best practices for AI-powered QA solutions, including prompts, context, tools, agent workflows and human-in-the-loop processes.
• Build mechanisms to evaluate AI output, measure quality and detect regressions.
• Monitor and improve the reliability, performance and cost of AI-powered solutions.
• Act as the technical focal point for AI within the QA team and help drive adoption, knowledge sharing and experimentation.
• Work closely with QA engineers and engineering teams to turn real-world challenges into practical solutions.

Requirements

• 5+ years of hands-on experience in Software Quality Engineering, Test Automation or Software Engineering.
• Strong experience with test automation frameworks such as Playwright, Cypress or similar.
• Strong programming skills in JavaScript/TypeScript or Python.
• Hands-on experience building AI-powered tools, applications, workflows or agents using LLMs.
• Practical understanding of agentic workflows, prompt and context engineering, tool calling, MCP and API integrations.
• Experience turning experimental solutions into reliable and maintainable engineering products.
• Strong QA fundamentals, including test design, regression testing and exploratory testing.
• Experience with APIs, databases and distributed systems.
• Experience with CI/CD systems such as GitHub Actions, Jenkins or similar.
• Strong problem-solving skills and ability to independently drive technical initiatives.

Nice to Have:

• Experience evaluating LLM or agent output and measuring AI solution quality.
• Experience building internal developer, engineering or QA platforms.
• Experience with observability and distributed systems.
• Experience integrating AI with tools such as GitHub, Jira, Confluence or CI/CD platforms.
• Experience with Kubernetes or cloud infrastructure.
• AdTech or programmatic advertising experience.