As a Lead for Voice AI systems, you will design and execute creative, large-scale testing strategies for in car voice assistants powered by ASR, TTS, NLU and LLMs. This role demands both technical depth and inventive thinking to validate non-deterministic AI behaviours across thousands of real-world scenarios. You will support, maintain, document, and enhance existing technology solutions by building tools to automate and improve system functions along with your team.

• Develop and maintain comprehensive test plans tailored for voice-based AI systems and in-car assistant platforms.

• Design test strategies for LLM-based interactions where predefined outputs don’t exist—leveraging creative thinking and scenario modelling to validate conversational accuracy, relevance, and safety.

• Define and execute test cases for speech-related components such as (ASR/NLU/TTS);

• Build tools and automation pipelines to evaluate thousands of voice interactions and LLM outputs for quality, stability, and edge-case behaviour.

• Collaborate with engineering and product teams to simulate real-world environments for in-car assistant testing.

• Analyse audio and text logs, spot anomalies, and systematically triage issues.

• Report defects with clarity and collaborate closely with developers to drive resolution.

• Build reusable testing components and contribute to internal QA frameworks and best practices.

• Occasionally lead quality-focused initiatives and drive improvements in test efficiency, coverage, and automation maturity.

• Bachelor’s/Master’s degree in Computer Science, Information Technology, or related disciplines.

• 6+ years of experience in manual and automation testing; prior experience testing AI/ML or voice based systems is a plus.

• Exposure to testing in automotive environments (In-vehicle Infotainment development) or other devices is an advantage.

• Experience testing APIs, custom web applications, or data-intensive systems is a strong advantage

• Managing Team and taking the ownership of Product delivery Preferred Skills

• Proficient in writing scripts using Python for test automation and data handling.

• Hands-on experience with test case design, bug tracking tools, and test management platforms.

• Strong analytical mindset with the ability to test beyond "expected results" and simulate nuanced user behaviours.

• Understanding of QA in the software development lifecycle (SDLC/STLC) and continuous delivery environments.

• Comfort with structured and unstructured test data generation and creative input crafting.

• Knowledge of logging/monitoring tools like Grafana, Kibana, or observability platforms is a plus.

• Excellent communication skills and strong collaboration mindset with cross-functional engineering teams.