Leads data engineering teams and provides technical direction for scalable, reliable data platforms and solutions. Oversees Agile delivery, backlog planning, operational support, quality standards, technical debt reduction, and stakeholder communication. Coaches engineers, sets performance goals, drives innovation, and guides adoption of data, cloud, containerization, DevOps, artificial intelligence, and machine learning technologies.

Designs, deploys, and operates production machine learning features, services, pipelines, and models. Owns ML systems from experimentation through monitoring while improving performance, reliability, scalability, and cost efficiency. Translates product requirements into ML solutions, solves complex technical problems, and influences design decisions. Develops LLM-based features such as prompt strategies, evaluation pipelines, chatbots, and agent workflows using appropriate frameworks.

Develops and maintains automated test frameworks and scripts for a Salesforce-based customer engagement platform. Translates requirements into test cases, creates BDD user stories using Cucumber and Java, executes automated tests, analyzes failures, reports defects, and repairs complex automation scripts. Collaborates with software engineers, participates in agile development and continuous improvement, conducts code reviews, and mentors less experienced engineers.