Teams at Groundswell

Build and operate secure batch and streaming data pipelines across structured, semi-structured, and legacy sources. Responsibilities include data ingestion, integration, quality validation, governance, monitoring, alerting, workflow orchestration, deployment automation, troubleshooting, and provenance management. Collaborate with engineering, cloud, data science, security, architecture, and customer teams to deliver reliable data products and AI-enabled workflows in regulated environments.

Build and operationalize production AI solutions for federal clients, from stakeholder discovery and architecture through evaluation, deployment, governance, monitoring, and optimization. Develop LLM applications using retrieval, structured outputs, tool use, and agentic workflows. Define quality metrics, create evaluation sets, document limitations, advise clients on AI use cases, and mentor engineers while contributing to reusable internal patterns and products.

Owns AI capabilities end to end, from stakeholder discovery and technical design through development, evaluation, deployment, monitoring, and documentation. Builds LLM applications using retrieval, structured extraction, tool use, and agent patterns; defines measurable quality criteria; balances accuracy, cost, latency, security, and complexity; supports client delivery and proofs of concept; and mentors engineers new to AI.