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Strong employer brand, Bangalore location, and mid-level AI role attract many qualified applicants.
Specialized LLM evaluation and production ML skills transfer across AI teams but require core ML experience.
Explicit 5+ years and specific LLM evaluation, production deployment, and tooling requirements create strict shortlisting.
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Lead and develop AI evaluation and quality engineering for Generative AI and ML systems, focusing on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems.
Design and implement scalable automated evaluation frameworks, observability standards, and AI quality metrics integrated with CI/CD pipelines for continuous validation.
Collaborate with cross-functional teams to deliver scalable, production-ready AI-powered applications ensuring alignment with Responsible AI principles and enterprise governance.
Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Engineering, or equivalent practical experience.
Minimum 5 years of hands-on experience delivering AI and ML systems into production.
Strong proficiency in Python, experience building automation frameworks, and deploying AI applications in production environments.
Experience with cloud-native application development on AWS, Azure, or GCP; expertise in AI evaluation frameworks, model quality measurement, and AI observability.
Deep expertise in AI and Generative AI concepts with a proven ability to apply industry best practices for evaluating and improving model performance at scale.
Experience leading complex AI evaluation projects and driving engineering process improvements focused on operational excellence.
Strong collaborator capable of working across distributed teams and mentoring others while connecting technical work to broader product and business goals.