• Collaborate with AI leaders, data scientists, ML engineers, and product teams to build agentic frameworks • Assist in building and refining AI agents using LLMs and multimodal models for tasks such as data exploration, scenario planning, and workflow automation • Design prompts and workflows that enable agents to reason, plan, and act autonomously • Work with structured and unstructured datasets, metadata and metrics definitions to create a contextual layer that enables agent performance • Conduct rigorous testing of agent capabilities, including edge cases and failure modes • Maintain detailed records of prompts, responses, agent iterations, and performance metrics • Work closely with cross-functional teams to align ML solutions with business goals and deployment requirements • Build, train, and evaluate ML models for tasks such as classification, regression, clustering, and anomaly detection • Clean, transform, and analyze structured and unstructured datasets to support model training and validation • Optimize models for accuracy, efficiency, and scalability using techniques like hyperparameter tuning and cross-validation • Maintain clear records of experiments, results, and insights for reproducibility and team knowledge sharing