Jobs at Gallatin AI, Inc.

Build and operate a Kubernetes-based data platform spanning lakehouse storage, ingestion, transformation, entity resolution, lineage, and data quality. Develop batch and streaming pipelines across heterogeneous and disconnected environments, create full-stack tools for subject matter experts, and expose documented APIs for applications and AI agents. Collaborate with product, AI/ML, infrastructure, mission partners, and field teams while mentoring engineers and supporting secure, air-gapped deployments.

Build and operate secure, production-grade infrastructure across Kubernetes, commercial and government clouds, edge appliances, classified networks, and air-gapped environments. Responsibilities include platform architecture, infrastructure coding, artifact pipelines, monitoring, incident response, security hardening, CVE remediation, STIG implementation, audit readiness, and DevSecOps improvement. Collaborate with Product, Engineering, GRC, and mission teams to support reliable deployments in IL5, IL6, and JWICS environments.

Build end-to-end fullstack features for logistics and national security systems. Responsibilities include developing performant APIs, creating relational data models, building data pipelines, collaborating with product and UX teams, writing tested production code, and improving CI/CD workflows. The role may involve classified environments and requires the ability to obtain and maintain a U.S. government security clearance.

Build and maintain Gallatin’s Vue-based Navigator frontend, including reusable UI components, design-system primitives, offline Progressive Web App functionality, API integrations, testing, and CI/CD improvements. Ensure reliable desktop and iPad experiences, troubleshoot API and CORS issues, contribute to architectural decisions, and collaborate with product, design, and backend teams. The role also involves documentation, demos, cross-functional troubleshooting, and potentially mentoring junior engineers.

Build, deploy, and operate AI/ML models, scalable MLOps pipelines, and real-time inference systems. Collect and process diverse data sources, improve training data quality, monitor model reliability and drift, and validate AI features with real-world users. The role also involves documenting best practices, mentoring teammates, and staying current with emerging AI technologies, LLMs, security risks, and model-development techniques.

Design, build, and scale reliable backend services, APIs, data pipelines, and integrations for an AI-driven logistics platform. Responsibilities include system architecture, database optimization, cloud deployment, container orchestration, monitoring, testing, documentation, code reviews, and cross-functional collaboration. The role also supports platform reliability, continuous improvement, and mentoring while contributing to national security and logistics missions.

Build and operate production ML infrastructure across cloud, on-premises, GPU, edge, and disconnected environments. Own model training and serving, CI/CD, reproducibility, evaluation, observability, data pipelines, retrieval systems, and secure IL5/IL6 deployments. Support accreditation and classified environments while improving reliability, quality, and performance of LLM and ML systems.

Design and ship interfaces for complex military logistics and AI systems. Conduct user research, prototype rapidly, collaborate with product and engineering teams, develop design systems, participate in design reviews, document specifications, and support product strategy. The role emphasizes human factors, information-dense interfaces, systems thinking, and designing for simulated and physical operational environments.