Senior AI Testing Engineer (Generative AI)
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Job Summary
Senior AI Testing Engineer (Generative AI)
Location India Remote / Hybrid / In-office specify your actual working model here
Experience 58 years total experience in software testing QA engineering or SDET roles with at least 23 years of meaningful hands-on exposure to Generative AI systems LLM applications or AI quality engineering.
Role Overview
We are looking for a Senior AI Testing Engineer to own quality across our Generative AI products and platform.
This role is fundamentally about engineering quality into AI systems not running test scripts. Youll design evaluation frameworks build automated testing pipelines and define what "good" looks like for LLM outputs RAG systems AI agents and voice AI applications. Youll work directly with AI engineers and product teams to make sure our systems are reliable safe and measurably improving over time.
If you understand how LLMs fail know how to catch hallucinations before users do and want to build the quality infrastructure that underpins production AI at scale this is the role.
Key Responsibilities
Evaluation Strategy & Frameworks
Design and own comprehensive testing strategies for Generative AI products including LLM applications RAG pipelines AI agents voice AI systems and workflow automation
Define evaluation methodologies covering functional testing response quality hallucination detection safety and guardrail testing prompt injection bias and toxicity retrieval quality latency benchmarking and agent workflow validation
Build reusable AI testing frameworks and automation pipelines for continuous evaluation
Create datasets benchmark suites and golden test sets for GenAI evaluation
Automated Evaluation
Develop automated evaluation pipelines using LLM-as-a-Judge and hybrid evaluation methods
Implement CI/CD-integrated AI evaluation pipelines
Drive observability and monitoring strategies for production AI systems
Quality Standards & Collaboration
Define measurable quality KPIs for AI systems
Establish testing standards best practices and governance processes for GenAI applications
Work closely with AI engineers product and platform teams to embed quality throughout the development lifecycle
Required Skills & Experience
Testing & Engineering Experience
58 years in software testing QA engineering SDET or test automation
23 years of hands-on experience testing or evaluating production-grade Generative AI or LLM-based systems
Strong test automation skills in Python
Experience designing scalable automated testing frameworks
Familiarity with API testing integration testing and performance testing
Generative AI Knowledge
Solid understanding of how LLM systems work and how they fail
Experience with RAG architectures prompt engineering AI agents embedding models and vector databases
Understanding of LLM evaluation methodologies and AI system failure modes
GenAI Testing Frameworks
Hands-on experience with at least one or more GenAI evaluation frameworks such as: DeepEval Ragas LangSmith Promptfoo TruLens OpenAI Evals or LangChain evaluation tools
Quality Engineering
Expertise in test strategy test planning test automation architecture defect lifecycle management and quality metrics
Ability to define and track measurable quality KPIs for AI systems
Preferred Qualifications
Experience with cloud platforms (AWS Azure or GCP)
Familiarity with MLOps / LLMOps workflows
Experience with CI/CD pipelines and DevOps practices
Exposure to monitoring and observability tooling for AI systems
Understanding of security and compliance for GenAI products
Experience with conversational AI or voice AI systems
Required Skills:
Senior AI Testing Engineer (Generative AI) Location India Remote / Hybrid / In-office specify your actual working model here Experience 58 years total experience in software testing QA engineering or SDET roles with at least 23 years of meaningful hands-on exposure to Generative AI systems LLM applications or AI quality engineering. Role Overview We are looking for a Senior AI Testing Engineer to own quality across our Generative AI products and platform. This role is fundamentally about engineering quality into AI systems not running test scripts. Youll design evaluation frameworks build automated testing pipelines and define what good looks like for LLM outputs RAG systems AI agents and voice AI applications. Youll work directly with AI engineers and product teams to make sure our systems are reliable safe and measurably improving over time. If you understand how LLMs fail know how to catch hallucinations before users do and want to build the quality infrastructure that underpins production AI at scale this is the role. Key Responsibilities Evaluation Strategy & Frameworks Design and own comprehensive testing strategies for Generative AI products including LLM applications RAG pipelines AI agents voice AI systems and workflow automation Define evaluation methodologies covering functional testing response quality hallucination detection safety and guardrail testing prompt injection bias and toxicity retrieval quality latency benchmarking and agent workflow validation Build reusable AI testing frameworks and automation pipelines for continuous evaluation Create datasets benchmark suites and golden test sets for GenAI evaluation Automated Evaluation Develop automated evaluation pipelines using LLM-as-a-Judge and hybrid evaluation methods Implement CI/CD-integrated AI evaluation pipelines Drive observability and monitoring strategies for production AI systems Quality Standards & Collaboration Define measurable quality KPIs for AI systems Establish testing standards best practices and governance processes for GenAI applications Work closely with AI engineers product and platform teams to embed quality throughout the development lifecycle Required Skills & Experience Testing & Engineering Experience 58 years in software testing QA engineering SDET or test automation 23 years of hands-on experience testing or evaluating production-grade Generative AI or LLM-based systems Strong test automation skills in Python Experience designing scalable automated testing frameworks Familiarity with API testing integration testing and performance testing Generative AI Knowledge Solid understanding of how LLM systems work and how they fail Experience with RAG architectures prompt engineering AI agents embedding models and vector databases Understanding of LLM evaluation methodologies and AI system failure modes GenAI Testing Frameworks Hands-on experience with at least one or more GenAI evaluation frameworks such as: DeepEval Ragas LangSmith Promptfoo TruLens OpenAI Evals or LangChain evaluation tools Quality Engineering Expertise in test strategy test planning test automation architecture defect lifecycle management and quality metrics Ability to define and track measurable quality KPIs for AI systems Preferred Qualifications Experience with cloud platforms (AWS Azure or GCP) Familiarity with MLOps / LLMOps workflows Experience with CI/CD pipelines and DevOps practices Exposure to monitoring and observability tooling for AI systems Understanding of security and compliance for GenAI products Experience with conversational AI or voice AI systems
Required Education:
MBA
