QA Lead

Optm Media Solutions; Bengaluru; On-site; INR 3,000,000 - 6,000,000; Full time

Job summary

Optm Media Solutions in Bengaluru seeks an experienced QA Lead to define and drive the quality strategy for a voice & AI platform. You will lead hands-on test automation across REST APIs, real-time services, and voice workflows, building scalable automation using Java and Python.

You will oversee performance testing with Locust/JMeter, and ensure robust CI/CD quality gates. The role requires strong leadership, cross-functional collaboration, and expertise in cloud-native architectures, QA for

Qualifications

• 8+ years of experience in Software Testing, Quality Engineering, or Test Automation with leadership responsibility.

Responsibilities

• Own and drive the overall Quality Engineering and Test Automation strategy across voice, cloud, and AI-powered applications.
• Design, develop, and maintain automated test frameworks for REST APIs, real-time services, SignalR/WebSocket communication, and end-to-end voice workflows.
• Build scalable and maintainable automation solutions using Java, Python, Selenium, Cucumber, or equivalent technologies.
• Lead performance, load, and scalability testing initiatives using Locust, JMeter, Gatling, or similar platforms to validate concurrency, latency, throughput, and system resilience.
• Establish robust automated regression suites and quality gates integrated into CI/CD pipelines.
• Define and implement testing strategies for speech recognition, transcription, translation, LLMs, conversational AI, and AI agent workflows.
• Partner with engineering, AI/ML, and platform teams to identify and mitigate quality risks across models, cloud services, integrations, and backend systems.
• Champion production-quality practices, including defect prevention, root cause analysis, observability, test coverage optimization, release readiness, and operational excellence.
• Drive Shift-Left testing practices and mentor QA engineers in modern Quality Engineering methodologies and automation best practices.
• Continuously improve engineering quality standards, metrics, and validation processes across the platform.

Skills

QA Leadership

Test Automation

API Testing

Distributed Systems Testing

CI/CD

Java

Python

Problem Solving

Communication

Tools

Selenium

Cucumber

Locust

JMeter

Gatling

WebSocket testing

Job description

QA Lead Voice & AI Platform:-

In this role, you will define and execute the quality strategy for our voice platform, cloud-based AI services, speech recognition solutions, and conversational AI applications. This is a hands‑on leadership role that combines test automation, API and integration testing, performance engineering, and AI/ML quality validation to ensure highly reliable, scalable, and production‑ready systems.

Key Responsibilities

• Own and drive the overall Quality Engineering and Test Automation strategy across voice, cloud, and AI-powered applications.
• Design, develop, and maintain automated test frameworks for REST APIs, real-time services, SignalR/WebSocket communication, and end‑to‑end voice workflows.
• Build scalable and maintainable automation solutions using Java, Python, Selenium, Cucumber, or equivalent technologies.
• Lead performance, load, and scalability testing initiatives using tools such as Locust, JMeter, Gatling, or similar platforms to validate concurrency, latency, throughput, and system resilience.
• Establish robust automated regression suites and quality gates integrated into CI/CD pipelines.
• Define and implement testing strategies for speech recognition, transcription, translation, Large Language Models (LLMs), conversational AI, and AI agent workflows, including accuracy, reliability, and regression validation.
• Partner closely with engineering, AI/ML, and platform teams to identify and mitigate quality risks across models, cloud services, integrations, and backend systems.
• Champion production‑quality practices, including defect prevention, root cause analysis, observability, test coverage optimization, release readiness, and operational excellence.
• Drive Shift‑Left testing practices and mentor QA engineers in modern Quality Engineering methodologies and automation best practices.
• Continuously improve engineering quality standards, metrics, and validation processes across the platform.

Required Qualifications

• 8+ years of experience in Software Testing, Quality Engineering, or Test Automation, including experience leading QA initiatives or teams.
• Strong hands‑on experience designing and building automation frameworks and API/integration test suites.
• Proficiency in Java, Python, or similar programming languages.
• Solid experience testing distributed systems, microservices architectures, cloud-native applications, and REST-based services.
• Hands‑on experience with performance and load testing tools such as Locust, JMeter, Gatling, or equivalent solutions.
• Experience implementing quality gates and automation within CI/CD environments.
• Strong understanding of test strategy, automation architecture, debugging, root cause analysis, and production‑quality engineering practices.
• Experience working with Azure or another major cloud platform.
• Excellent problem‑solving, communication, and cross‑functional collaboration skills.

Preferred Qualifications

• Experience testing speech recognition, conversational AI, generative AI, LLM-based applications, or AI‑agent workflows.
• Experience validating real‑time communication systems, voice platforms, streaming systems, or WebSocket-based services.
• Familiarity with Azure AI Services, OpenAI services, cloud observability, and distributed system monitoring.
• Experience with containerized environments and modern DevOps practices.

What We're Looking For

We are looking for a hands‑on Quality Engineering leader who goes beyond traditional functional testing. The ideal candidate is passionate about automation, quality at scale, and building reliable systems. You should be comfortable validating distributed cloud architectures, testing real‑time voice experiences, performing meaningful performance and scalability validation, and establishing strong quality gates for AI-powered applications.

Success in this role requires close collaboration with software engineers, platform teams, and AI/ML engineers to identify issues early, automate what matters most, and continuously improve the reliability, scalability, and customer experience of our Voice and AI Platform.