🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
Cookies & analytics consent
We serve candidates globally, so we only activate Google Tag Manager and other analytics after you opt in. This keeps us aligned with GDPR/UK DPA, ePrivacy, LGPD, and similar rules. Essential features still run without analytics cookies.
Read how we use data in our Privacy Policy and Terms of Service.
🤖 15+ AI Agents working for you. Find jobs, score and update resumes, cover letter, interview questions, missing keywords, and lots more.
LeadSquared • Bengaluru, Karnataka, India
Role & seniority: Quality Engineer (QE), 2–4 years experience; focused on QA for Voice AI platforms.
Stack/tools: Automation testing with Python (preferred) or similar scripting; API/backend testing; CI/CD integration; familiarity with SIP, WebSocket, WebRTC; real-time/telephony and Voice AI pipelines (STT → NLU → Response generation → TTS).
Design and execute end-to-end, functional, integration, regression, and exploratory tests for voice workflows and telephony integrations.
Build/maintain automation suites for APIs, backend services, and voice scenarios; integrate tests into CI/CD; log and track defects with root-cause analysis.
Validate AI responses, non-functional aspects (latency, reliability, concurrency), and continuously improve test coverage, data, and frameworks.
2–4 years in QA/test automation
Python automation (or similar), strong testing fundamentals (functional/integration/regression/system)
Experience testing backend systems and APIs
Knowledge of Voice AI pipelines (STT → NLU → Response generation → TTS)
Real-time communication protocols (SIP, WebSocket, WebRTC) and event-driven systems
CI/CD workflow familiarity; strong debugging/analytic/communication skills
Telephony concepts (IVR, call routing, RTP)
Audio quality testing (jitter, packet loss) and concurrency
Cloud experience (AWS/GCP); performance/load testing tools
Experience validatin
Job Title: Quality Engineer (QE) – Voice AI
Experience: 2–4 Years Role Overview We are looking for a Quality Engineer (QE) to ensure the quality, reliability, and performance of our end-to-end Voice AI platform. This role focuses on testing real-time voice workflows, telephony integrations, AI-driven conversations, and backend systems using a strong automation-first approach. You will work closely with Backend, AI, and Product teams to validate that voice interactions behave correctly across real-world scenarios, edge cases, and scale conditions. Key Responsibilities
Test end-to-end Voice AI workflows, including call initiation, speech recognition, intent handling, conversational logic, responses, fallbacks, and call termination
Design and execute functional, integration, regression, and exploratory tests for voice-based systems
Build and maintain automation test suites for APIs, backend services, and voice workflows
Validate telephony integrations including call flows, retries, failures, timeouts, and disconnect scenarios
Validate AI-generated responses for accuracy, consistency, and error handling
Perform non-functional testing including latency, reliability, and concurrency validation
Integrate automated tests into CI/CD pipelines
Log, track, and analyze defects; collaborate with developers for root-cause analysis
Continuously improve test coverage, test data, and automation frameworks
Required Skills & Experience
2–4 years of experience in Quality Engineering / QA / Test Automation
Strong experience in automation testing using Python (preferred) or similar scripting languages
Solid understanding of software testing fundamentals (functional, integration, regression, system testing)
Experience testing backend systems and APIs
Understanding of Voice AI pipelines: (STT → NLU → Response generation → TTS)
Hands-on experience testing Voice AI, conversational AI, or chatbot systems
Understanding of real-time communication protocols and systems: (SIP , WebSocket , WebRTC)
Familiarity with real-time or event-driven systems
Understanding of CI/CD pipelines and automated test execution
Strong analytical, debugging, and communication skills
Nice to Have / Bonus Skills
Deeper exposure to telephony systems (IVR, call routing, RTP concepts)
Experience validating audio quality, jitter, packet loss, and concurrency scenarios
Familiarity with cloud environments (AWS/GCP)
Experience with performance or load testing tools
Experience testing AI edge cases such as hallucinations, retries, and fallback handling
You Might Thrive If You
Think beyond UI testing and enjoy validating complex backend and real-time systems
Can design tests that simulate real customer voice interactions
Prefer automation-first quality engineering
Are comfortable working in fast-moving Voice AI environments
Collaborate closely with backend and AI engineers to improve system quality
Why This Role
Work on production Voice AI systems
Own quality for mission-critical, real-time voice workflows
Build deep expertise in Voice AI testing, telephony, and automation
High ownership and high-impact role
Show more Show less