Live opening · Posted 7 days ago

Software Quality Engineer – Conversational AI / LLM Testing

Cognizant · Chennai, Tamil Nadu, India (Hybrid)
Linkedin No
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At a glance

The key details from the original listing.

Posted 7 days ago
CompanyCognizant
LocationChennai, Tamil Nadu, India (Hybrid)
Work modeNo
SourceLinkedin
Listed7 days ago

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About the role

Description supplied by the original job listing.

Experience: 4-9 Years
Location : Noida / Kolkata
Domain : Airlines / Travel Technology
Job Summary
We are seeking a highly skilled Software Quality Engineer with hands-on experience in testing Conversational AI, LLM-based applications, chatbots, virtual assistants, and Agentic AI systems. The ideal candidate will have a strong automation and quality engineering background, deep understanding of how modern conversational systems operate, and solid experience within the Airline or Travel domain, particularly around Booking, Post-Booking, and Check-In workflows.
This role involves validating AI-driven customer conversation journeys, ensuring response quality, evaluating non-deterministic outputs, and establishing robust testing strategies for intelligent systems.
Key Responsibilities
Own and drive the quality strategy for conversational AI products and customer-facing virtual assistants.
Design, execute, and automate test scenarios for LLM-powered applications, chatbots, voice assistants, RAG-based systems, and agentic workflows.
Validate conversational flows across booking, post-booking servicing, and check-in experiences within airline and travel ecosystems.
Develop and maintain automated test frameworks using Python.
Create test datasets, golden datasets, and evaluation benchmarks to measure AI system performance.
Design evaluation mechanisms for non-deterministic AI outputs using:
Rubric-based scoring
LLM-as-a-Judge approaches
Human review workflows
Statistical quality assessment methods
Validate prompt behavior, context retention, retrieval accuracy, tool/function calling, and response consistency.
Identify conversational AI failure modes such as hallucinations, context loss, prompt injections, retrieval issues, and reasoning errors.
Collaborate with Product Managers, Data Scientists, AI Engineers, and Developers to improve system quality and reliability.
Participate in release validation, regression testing, performance testing, and production quality monitoring.
Mandatory Skills & Qualifications
Quality Engineering
4+ years of experience in Software Quality Engineering, QA Automation, or SDET roles.
Proven experience owning the quality of a product or platform from testing strategy to production validation.
Strong understanding of software testing methodologies, automation frameworks, and quality metrics.
Python Automation
Strong scripting and automation expertise in Python.
Experience developing automated test suites, validation scripts, and data-driven testing frameworks.
Conversational AI / LLM Testing
Hands-on Experience Testing One Or More Of The Following
Large Language Model (LLM) applications
Conversational AI platforms
Chatbots and Virtual Assistants
Voice Assistants
Retrieval Augmented Generation (RAG) solutions
Agentic AI applications
AI/LLM Evaluation Expertise
Practical Understanding Of
Prompt engineering principles
Context windows and memory handling
Function/Tool Calling
Retrieval pipelines
LLM evaluation methodologies
AI quality metrics and benchmarking
Experience With
Golden datasets
Human evaluation workflows
Statistical validation approaches
Non-deterministic output testing
Domain Knowledge
Strong Experience In Airline Or Travel Domain, Including
Flight Booking journeys
Reservation Management
Post-Booking Services
Check-In processes
Passenger servicing workflows
Preferred Skills
Experience with OpenAI, Azure OpenAI, Anthropic, Gemini, or similar AI platforms.
Understanding of NLP concepts and conversational design.
Exposure to API testing and automation tools.
Experience with CI/CD pipelines and test automation integration.
Knowledge of cloud platforms (Azure, AWS, GCP).
Familiarity with observability and monitoring tools for AI applications.

Work arrangement
No

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