AI QA Engineer

Immediate joiners required !! 2 days WFO - Hinjewadi Phase 3 Who are we Fulcrum Digital is an agile and next-generation digital accelerating company providing digital transformation and technology services right from ideation to implementation. These services have applicability across a variety of industries, including banking & financial services, insurance, retail, higher education, food, healthcare, and manufacturing. Key Responsibilities Design and execute test cases for LLM agents, RAG pipelines, agentic workflows, and AI-assisted decision tools Validate AI outputs against ground truth using structured accuracy scoring (NAICS, risk exposure flags, hazard group mapping) Detect hallucinations, reasoning gaps, source fabrication, and misattributions in model-generated content Run multi-model comparative testing across GPT, Claude, Gemini, and Perplexity — evaluating accuracy, latency, and output completeness Test prompt versions iteratively and track accuracy changes across prompt cycles Validate citation accuracy, document ingestion pipelines, and cross-document context handling Design edge case and negative tests for AI-specific failure modes — content filter triggers, tool call limits, missing documents, and incomplete synthesis Perform regression testing after model upgrades, prompt changes, and backend fixes, and maintain structured QA sign-off in JIRA What Makes This Role Different from Traditional QA You evaluate whether an AI is reasoning correctly — not just whether the UI behaves as expected You build evaluation rubrics for non-deterministic outputs and apply LLM-as-a-Judge techniques to score quality at scale You treat every model or prompt change as a potential accuracy regression, not just a functional one You understand that in live AI systems, a passing test today does not guarantee a passing test tomorrow Required Skillsets 7–8 years of QA experience with minimum 2 years in Generative AI / LLM-based projects Hands-on experience testing chatbots, RAG systems, or agentic AI pipelines Proven ability to perform ground truth validation and detect hallucinations and reasoning failures Familiarity with multi-model evaluation, prompt-aware testing, and JIRA-based defect reporting Preferred Skillsets Background in insurance or regulated industries; exposure to underwriting or risk classification concepts Familiarity with Azure OpenAI, AWS Bedrock, or SharePoint-integrated AI environments Knowledge of AI governance, content filtering, and PII redaction validation