QA Engineer (AI experience)

What is the project, and why should you care?

This is an innovative AI-driven personal assistant platform designed to function as a “second brain,” helping users capture, organize, and analyze their life experiences.

We are developing an MVP that includes voice recording, transcription, and data analysis, with a long-term vision of evolving into a personalized digital twin.

Our team is seeking an experienced QA professional with AI testing expertise to ensure reliability, accuracy, and trust in the product’s intelligent features.

You will be an excellent fit for this position if you have:

General QA Skills

• 4+ years of professional experience in Quality Assurance.
• Experience with mobile (iOS/Android) and web application testing.
• Strong knowledge of test design techniques, test case creation, and defect lifecycle management.
• Hands-on with tools like Postman, JMeter
• Understanding of modern software development practices (Agile/Scrum/Kanban).

AI/ML-Specific QA

• Experience testing AI/ML-based applications (e.g., LLMs, voice recognition, NLP, embeddings, vector search).
• Familiarity with LLM evaluation methods (accuracy, hallucination rate, response relevance).
• Ability to validate speech-to-text and text-to-speech quality (e.g., Whisper, DeepSpeech, Azure Cognitive Services).
• Knowledge of AI fairness, bias, explainability, and privacy testing considerations.
• Comfortable working with test datasets for NLP and conversational AI validation.
• Basic familiarity with vector DBs (e.g., Pinecone, Qdrant) and their testing patterns.

Soft Skills

• Analytical mindset with attention to detail.
• Strong communication and documentation skills.
• Proactive in spotting risks and proposing solutions.
• Curious about new AI quality frameworks and responsible AI testing practices.

Here are some of the things you’ll be working on:

• Define and execute a QA strategy for AI-powered features.
• Develop and maintain a manual for mobile and backend services.
• Validate LLM responses, speech recognition accuracy, and AI-driven workflows.
• Collaborate closely with Product Owner, Python developers, and Mobile engineers to align QA scope.
• Conduct exploratory testing of agent orchestration, contextual memory, and personal assistant flows.
• Monitor performance, latency, and stability of AI integrations.
• Ensure compliance with privacy-first AI practices (data minimization, encryption, GDPR).
• Document defects clearly and work with the team to drive resolution.
• Support release readiness by validating builds and participating in sprint reviews/demos.