Middle QA Engineer (AI and No-Code)

At iSpeedToLead, we’re reinventing the PropTech world with AI-powered SaaS solutions and no-code automation. We’re looking for a hands-on QA Engineer who’s ready to dive deep into testing LLM prompts and AI workflows - and help us scale quality across everything we build.

Must-have skills:

• 3+ years in QA, including 1+ year testing AI solutions.
• Hands-on experience testing LLM prompts.
• Strong skills in no-code workflow testing (Make, n8n, Zapier).
• Understanding of basic ML/DL concepts, model types (e.g., classification, regression, clustering), and how they apply in AI products.
• Understanding of A/B testing principles to compare the performance of different AI models or features.
• Experience with REST API, Postman, JSON.
• Ability to create test cases, checklists, and plans for AI & automation.
• Comfortable with user flows, project documentation, and task tracking.
• Basic project management mindset: prioritization, acceptance criteria, communication.

Nice-to-have:

• Experience working with cloud platforms (AWS, Google Cloud) and their AI/ML services.
• Experience with BigQuery / MongoDB / PostgreSQL.
• Knowledge of Bubble.io.
• Familiarity with TestRail or Allure.
• Understanding of CI/CD.
• Experience with Sentry logs.

What you’ll be doing:

• Test and refine LLM prompts (GPT, Claude, Gemini) - ensuring stability, accuracy, and edge-case handling.
• Debug & improve automation workflows in Make, n8n, Zapier.
• Design and execute tests using various datasets, including synthetic, real, and edge-case data.
• Participate in AI solution design from a quality perspective.
• Identify and assess risks associated with AI implementation (e.g., security, privacy, reliability).
• Monitor data and model quality using tools like Deepchecks or Evidently AI.
• Test AI model safety and fairness using tools like Giskard.
• Work with REST APIs, Postman, JSON to validate integrations.
• Monitor system stability: Webhooks, Airtable, Notion, OpenAI, APIs.