Senior AI/Data Engineer needed to architect and deliver enterprise data platforms, machine learning systems, and applied AI applications for federal agencies and other clients. You will lead the design, implementation, and governance of data pipelines, ML/AI solutions, and engineering standards, collaborating with client leadership, architects, data scientists, and governance teams. This is a remote position based in Mount Pleasant, South Carolina, United States, with occasional travel to client sites as required. Responsibilities include architecting and delivering data platforms and pipelines on Azure (Data Lake Storage, Azure SQL, Data Factory, Microsoft Fabric/Foundry) or equivalent cloud services; setting standards for ETL design, schema enforcement, data validation, quality checks, and data lineage; designing, building, and deploying ML/AI solutions including applications built on large language models such as retrieval-augmented generation, document understanding, and agentic workflows; building secure API endpoints and microservices for analytics and ML platforms; establishing MLOps practices (experiment tracking, model registries, CI/CD, containers, monitoring, cost and performance tuning); applying data and AI governance for compliance, reproducibility, auditability, and responsible AI, including federal frameworks like the NIST AI Risk Management Framework; translating mission and business needs into technical roadmaps, estimates, and briefings for client leadership; mentoring engineers and data scientists and leading technical work across multidisciplinary teams

Senior AI/Data Engineer needed to architect and deliver enterprise data platforms, machine learning systems, and applied AI applications for federal agencies and other clients. You will lead the design, implementation, and governance of data pipelines, ML/AI solutions, and engineering standards, collaborating with client leadership, architects, data scientists, and governance teams. This is a remote position based in Mount Pleasant, South Carolina, United States, with occasional travel to client sites as required. Responsibilities include architecting and delivering data platforms and pipelines on Azure (Data Lake Storage, Azure SQL, Data Factory, Microsoft Fabric/Foundry) or equivalent cloud services; setting standards for ETL design, schema enforcement, data validation, quality checks, and data lineage; designing, building, and deploying ML/AI solutions including applications built on large language models such as retrieval-augmented generation, document understanding, and agentic workflows; building secure API endpoints and microservices for analytics and ML platforms; establishing MLOps practices (experiment tracking, model registries, CI/CD, containers, monitoring, cost and performance tuning); applying data and AI governance for compliance, reproducibility, auditability, and responsible AI, including federal frameworks like the NIST AI Risk Management Framework; translating mission and business needs into technical roadmaps, estimates, and briefings for client leadership; mentoring engineers and data scientists and leading technical work across multidisciplinary teams