Partner with Data and Product to identify and execute AI opportunities aligned with strategic objectives.
Establish and enforce AI and machine learning and data operational standards, governance, and best practices across the organization.
Deliver actionable, data-driven insights and reporting to inform business decisions and evaluate performance across products, operations, and AI systems.
Build reliable experimentation frameworks to validate model performance and business impact and drive iterative improvements through reliable model evaluation and testing.
Own the scalability, robustness, observability, optimization and operational excellence of production AI systems and data pipelines.
Requirements
Minimum of 3-5 years of designing, building, and operationalizing end-to-end data and AI systems in production environments
Sound knowledge of machine learning lifecycle from data gathering and data preparation to feature engineering to model deployment, monitoring and iteration.
Hands-on experience with LLM-based systems (e.g., RAG architectures, prompt engineering, model evaluation, API integration).