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Techgenzi Private Limited • Bengaluru, Karnataka, India
Role & seniority: QA Lead / Senior QA Engineer for AI Systems
Stack/tools: Backend and API testing; automation frameworks; AI/ML-driven apps; LLMs, prompts, RAG pipelines; monitoring/observability; performance metrics
Lead end-to-end QA for AI/GenAI features across the product stack
Design/testing strategies for LLMs, prompts, RAG pipelines, and probabilistic/non-deterministic systems
Build and maintain automation frameworks across APIs, UI, and AI layers; drive production reliability and cross-functional quality delivery
Extensive QA/Test Engineering experience
Strong API and backend testing methodologies
Test strategy development and automation implementation
Experience with AI/ML/Generative AI systems and probabilistic outputs
Experience testing LLMs and RAG-based apps
Cloud familiarity (AWS or Azure)
Startup or product-driven environment background
Knowledge of performance, scalability, and cost-optimization testing
Location & work type: Location not specified; work type not specified in description (implied full-time, production-grade AI product focus)
Description
QA Lead / Senior QA Engineer AI Systems
Role Overview
We are seeking a highly skilled and strategic QA Lead / Senior QA Engineer to drive end-to-end quality assurance for our AI and Generative AI systems. This role will be responsible for defining quality standards, designing evaluation frameworks for non-deterministic AI systems, and ensuring reliability across AI-powered products.
The ideal candidate brings strong expertise in backend and API testing, automation frameworks, and hands-on experience working with AI/ML-driven applications. You will work closely with engineering teams and leadership to embed quality at every stage of the product lifecycle.
Key Responsibilities
Lead end-to-end quality assurance for AI and GenAI features across the product stack Design and execute testing strategies for LLMs, prompts, RAG pipelines, and AI-driven workflows Develop evaluation methodologies for probabilistic and non-deterministic systems Build and maintain automation frameworks across APIs, UI, and AI layers Drive production reliability through monitoring, observability, and performance metrics Collaborate cross-functionally with engineers, product teams, and leadership to ensure quality-first delivery
Required Qualifications
58 years of experience in Quality Assurance or Test Engineering Strong expertise in API and backend testing methodologies Proven experience in test strategy development and automation implementation Exposure to AI, Machine Learning, or Generative AI systems Ability to evaluate and test systems with probabilistic outputs
Preferred Qualifications
Experience testing LLM and RAG-based applications Familiarity with cloud platforms such as AWS or Azure Prior experience in startup or product-driven environments Knowledge of performance, scalability, and cost optimization testing
Why Join Us
Opportunity to shape AI quality practices from the ground up Work on impactful, production-grade AI products High ownership, autonomy, and visibility within a fast-moving environment
(ref: hirist.tech)