Teams at Groundswell

Lead infrastructure and platform engineering teams, oversee capacity, schedules, risks, governance, and delivery quality. Design secure, scalable AWS architectures and external integrations; translate business needs into technical roadmaps and implementation plans. Establish standards for data integration, configuration, compliance, and auditability. Guide Agentic Audit technology evolution, evaluate emerging technologies, conduct technical and code reviews, and support platform deployments in a DevSecOps environment.

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.