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Tier-1 employer, metro Bengaluru location, and mid-level AI role increase applicant competition.
Specialized LLM evaluation and RAG focus increases domain specificity but remains transferable across AI-product companies.
Explicit 5+ years, mandatory ML/LLM production experience, Python and cloud deployment requirements tighten screening.
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Lead AI evaluation and quality strategy for Generative AI, LLMs, Retrieval-Augmented Generation (RAG) systems, and agentic workflows.
Design and implement scalable automated evaluation frameworks integrated into CI/CD pipelines to ensure AI system reliability, safety, and performance.
Collaborate cross-functionally to develop AI-powered applications, maintain observability, and uphold Responsible AI principles in production environments.
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Engineering, or equivalent experience.
5+ years of hands-on experience delivering AI and Machine Learning-powered production systems.
Strong proficiency in Python and experience building automation frameworks and testing infrastructure.
Experience with cloud-native AI application deployment on AWS, Azure, or Google Cloud and AI model evaluation or validation frameworks.
Experienced in applying AI/ML evaluation methodologies with measurable impact on model quality and system reliability in production.
Comfortable leading technical projects involving complex AI systems including LLMs, RAG, and agentic workflows with cross-functional stakeholders.
Demonstrates strong analytical decision-making aligned with product and business goals and advances engineering best practices in AI quality and observability.