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Birlasoft • India
Role & seniority: Testing Lead (Grade 5B), Mid-Senior level, Full-time
Stack / tools: Python (PyTest/UnitTest), API testing, LLM/RAG pipelines, embeddings, data workflows, vector databases, agentic AI frameworks, Azure (preferred), CI/CD/DevOps testing
Define and implement testing strategies for GenAI/Agentic AI (LLMs, RAG, non-deterministic behavior, prompt injections, evaluation metrics)
Validate multi-step agent workflows (tool orchestration, memory, retries, guardrails) and end-to-end RAG/LLM pipelines
Build/maintain test automation and AI-assisted testing (synthetic data, regression suites), ensure performance, reliability, and responsible AI compliance; mentor junior testers
7–9 years QA/testing experience; hands-on AI/ML or GenAI testing
Experience testing APIs, data pipelines, and LLM-based systems
Experience with RAG systems and vector databases
Exposure to agentic AI frameworks and Azure/cloud platforms
CI/CD and DevOps testing exposure
Location & work type: Location not specified; Full-time role
Area(s) of responsibility
Job Description
Testing Lead – Agentic AI & Generative AI Platforms (Grade 5B)
Role Summary
We are seeking a Testing Lead (Grade 5B) with strong hands-on expertise in testing Agentic AI and Generative AI platforms. The role requires deep understanding of GenAI systems, data structures, data pipelines, and automation. The Testing Lead will design and execute AI-centric test strategies for LLM-based applications, RAG pipelines, autonomous agents, APIs, and data workflows while mentoring junior team members.
Key Responsibilities
GenAI & Agentic AI Testing Strategy
Define and implement testing strategies for GenAI and Agentic AI solutions including LLMs and RAG systems.
Design test approaches for non-deterministic AI behavior such as hallucinations, bias, and prompt injections.
Establish evaluation metrics beyond exact-match validation.
Agentic AI & Workflow Validation
Validate multi-step agent workflows including tool orchestration, memory, retries, and guardrails.
Ensure predictable behavior and controlled variability in autonomous agents.
RAG, LLM & Model Validation
Validate RAG pipelines end-to-end including ingestion, chunking, embeddings, retrieval, and grounding.
Test LLM responses across single-turn, multi-turn, and regression scenarios.
Test Automation & AI-Assisted Testing
Build and maintain automation using Python frameworks such as PyTest or UnitTest.
Automate API testing, data validation, and regression suites.
Leverage AI-assisted testing techniques such as synthetic data generation.
Performance, Reliability & Responsible AI
Conduct performance and scalability testing for inference, agents, and APIs.
Validate responsible AI requirements including bias, drift, security, and compliance.
Collaboration & Mentorship
Mentor junior testers and review test artifacts.
Collaborate with architects, data scientists, and engineers to embed quality early.
Must-Have
Required Skills & Experience
7–9 years of experience in QA / Testing Hands-on experience in AI/ML or GenAI testing Experience testing APIs, data pipelines, and LLM-based systems
Good-to-Have
Experience with RAG systems and vector databases Exposure to Agentic AI frameworks and cloud platforms (Azure preferred) CI/CD and DevOps testing exposure
Education
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related fields.
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How many agentic AI / Gen AI projects have you worked on ? How is testing an AI / GenAI application different from testing a traditional software application? What types of testing would you perform for APIs or data pipelines in an AI‑based system? Why are data quality and validation critical when testing AI or GenAI systems?
Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries IT Services and IT Consulting