Teams at E Source

Owns end-to-end delivery of production data platforms for utility clients, including discovery, architecture, ingestion, transformation, orchestration, governance, quality, deployment, and handover. Uses Databricks, Spark, Python, SQL, and AWS to modernize legacy systems, integrate utility data sources, build observable pipelines, and deliver operator-facing applications. Leads client engagements, manages scope and timelines, supports migrations, and contributes reusable engineering frameworks and reference architectures.

Build and deploy production generative AI and machine learning systems for utility clients. Own engagements end to end, including discovery, architecture, retrieval, model selection, evaluation, deployment, monitoring, operator-facing applications, and post-go-live support. Integrate with client data and business systems, establish AI safety and governance controls, manage scope and risk, and communicate with technical teams and executives. Contribute reusable accelerators, evaluation frameworks, and reference architectures across client engagements.

Lead complex AMI and utility technology projects from planning through implementation. Manage schedules, budgets, resources, vendors, risks, issues, dependencies, reporting, governance, invoicing, and client expectations. Coordinate utility teams, technical specialists, vendors, system integrators, and field contractors across deployment, integration, testing, data readiness, operational readiness, and change management workstreams. Facilitate executive communication, resolve challenges, and maintain project momentum across distributed teams.