AI Assurance Architect

Virtusa; Maharashtra; On-site; INR 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Healthcare stipend

Job summary

Virtusa in Maharashtra, India, is seeking a GenAI-driven QA specialist to identify the most effective architectures and models for solving complex data problems in Quality Engineering and to spearhead innovative testing strategies.

You will apply GenAI to automate STLC tasks, validate LLM-based systems, assess performance, security, finetuning, bias, and explainability, and lead improvements across projects.

Responsibilities

• Identify the most effective architectures and models to solve complex data problems around Quality Engineering using GenAI
• Apply GenAI in automating different aspects of STLC such as Test artefact generation, defect prediction, defect triaging, failure analysis, test optimization and self-healing.
• GenAI systems validation including RAG based LLMs for Q&A, generated content and recommendations
• Validate performance, security, finetuning and feedback function for LLM based applications
• Build solutions to ensure fairness and trustworthiness of GenAI systems by performing automated tests for prompt safety, response accuracy, relevancy, toxicity, biasness and explainability
• Lead, mentor, and advise the team members in deploying LLMs and AI models for specified use cases
• Document, summarize and present findings and recommendations for Continuous improvement of AI/GenAI implementations across Quality Assurance & Quality Engineering

Job description

• Identify the most effective architectures and models to solve complex data problems around Quality Engineering using GenAI
• Apply GenAI in automating different aspects of STLC such as Test artefact generation, defect prediction, defect triaging, failure analysis, test optimization and self-healing.
• GenAI systems validation including RAG based LLMs for Q&A, generated content and recommendations
• Validate performance, security, finetuning and feedback function for LLM based applications
• Build solutions to ensure fairness and trustworthiness of GenAI systems by performing automated tests for prompt safety, response accuracy, relevancy, toxicity, biasness and explainability
• Lead, mentor, and advise the team members in deploying LLMs and AI models for specified use cases
• Document, summarize and present findings and recommendations for Continuous improvement of AI/GenAI implementations across Quality Assurance & Quality Engineering