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.

Supports AMI and utility technology implementations through test strategy development, requirements traceability, test execution, defect resolution, data-flow validation, and data-quality reviews. Analyzes system exceptions and operational reports, validates meter and installation records, and helps establish sustainable data-management, quality-assurance, remediation, and escalation processes. Provides documentation, training, coaching, and implementation support to utility clients, vendors, integrators, and field teams.