QE GenAI Architect (14+ Years Experience) – UST | Any Location
UST
2 - 5 years
Bengaluru
Posted: 13/01/2026
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Job Description
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CCTC | ECTC | Notice Period | Location Preference
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Key Responsibilities
- Architect end-to-end GenAI-powered QE frameworks integrating LLMs, autonomous testing agents, and intelligent validation techniques.
- Develop AI-driven test generation, self-healing scripts , and automated defect classification engines.
- Lead QE strategy across large enterprise programs, ensuring scalability, performance, and accuracy of automation systems.
- Partner with product, engineering, and data science teams to embed AI/ML into SDLC and create continuous quality pipelines.
- Evaluate emerging LLMs, vector databases, RAG workflows, and MLOps platforms for QE optimization.
- Build reusable, modular accelerators for AI-Augmented Regression, API validation, UI automation, and data intelligence .
- Mentor QE teams on GenAI adoption, automation best practices, and architectural governance.
- Drive innovation, solutioning, workshops, and customer presentations as a QE thought leader.
Must-Have Skills
- 14+ years of QE experience with at least 35 years in GenAI/LLM-based automation .
- Expertise in Python, Java, or JavaScript with hands-on experience building automation frameworks.
- Strong understanding of LLMs (GPT, Claude, Llama, etc.), vector stores (FAISS, Pinecone), RAG pipelines , embeddings, and prompt engineering.
- Proven experience with AI-driven test generation, autonomous test agents, and intelligent defect prediction .
- Hands-on experience with Selenium, Playwright, API automation , and CI/CD test orchestration.
- Deep familiarity with cloud platforms (AWS, Azure, or GCP ) and container ecosystems (Docker/Kubernetes ).
- Strong architectural mindset with the ability to design scalable automation platforms.
Good-to-Have Skills
- Experience in MLOps , data pipelines, or AI model evaluation frameworks.
- Knowledge of GenAI observability, model drift detection, and guardrails .
- Experience with Performance Engineering , Chaos Testing, or Security Testing automation.
- Prior consulting or customer-facing architecture leadership roles.
- Experience building reusable AI accelerators for enterprise teams.
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