• Architect, build, and manage robust data pipelines and infrastructure that support large-scale AI and machine learning initiatives. • Develop and optimize integrations between core AI services, including AWS Bedrock, LLMs, and internal platforms (Salesforce, Tableau, Slack) for enhanced operational performance. • Collaborate with applied scientists and ML engineers to refine model deployments, feature engineering, and ensure seamless operationalization of predictive and conversational AI solutions. • Implement advanced data processing and real-time analytics workflows for conversational intelligence, sentiment analysis, and predictive troubleshooting. • Ensure high-quality data management, emphasizing security, compliance, data governance, and maintainability within AI-driven environments. • Drive tooling and infrastructure solutions that facilitate efficient testing, debugging, monitoring, and continuous improvement of AI applications. • Establish comprehensive observability frameworks (logs, metrics, alerts) to maintain system reliability, performance, and operational insights. • Participate actively in technical discussions, code reviews, and strategic planning to align AI infrastructure development with business goals. • Proto-type and develop intuitive, user-friendly UI screens and dashboards that enable customer success teams to leverage AI-driven insights effectively.