Teams at Rackner

Own and evolve a secure, cloud-native internal developer platform for a federal health mission. Responsibilities include Terraform and GitOps foundations, multi-tenant Kubernetes on AWS GovCloud, self-service onboarding, MLOps/AIOps, data lakehouse enablement, observability, security automation, compliance artifacts, documentation, and stakeholder partnership. The role requires senior ownership of production platforms and offers opportunities for technical leadership.

Build, evaluate, integrate, and operationalize machine learning, deep learning, and generative AI capabilities for federal mission applications. Responsibilities include developing models and datasets, creating AI services and interfaces, integrating APIs and pipelines, deploying scalable and reproducible solutions, documenting workflows, and improving capabilities through technical and user feedback. The role collaborates with software and data engineers, technical leaders, subject-matter experts, and mission users in a controlled government environment.

Build and deploy AI applications, agents, intelligent workflows, document-processing solutions, predictive analytics, and automation. The role spans AI use-case assessment, solution design, prototyping, evaluation, testing, production deployment, monitoring, governance, and responsible-AI controls. The engineer will integrate AI with enterprise systems, APIs, workflows, and data platforms while partnering with engineering, cybersecurity, governance, and mission teams in a federal environment.