Design, build, and maintain mission-critical data storage and integration components for the Defense Health Agency. This includes optimizing database performance, managing security controls, and ensuring robust disaster recovery strategies.
Rackner
12 Remote Job Openings at Rackner
The role involves partnering with stakeholders to gather data requirements and translating them into technical deliverables and dashboards. You will analyze integrated datasets to provide operational insights and validate data quality within a federal healthcare environment.
Healthcare Data Strategy & Insights Analyst (DoD Secret | Remote)
Rackner
·
Full Time
·
2 days ago
Rackner
The role involves partnering with stakeholders to gather data requirements and translating them into actionable insights and dashboards. You will also validate integrated datasets and optimize data workflows to support leadership decision-making in a federal healthcare environment.
Design and maintain end-to-end data pipelines to transform raw military healthcare data into actionable intelligence. Collaborate with DevSecOps and Data Science teams to deliver AI-ready datasets while ensuring compliance with DoD and NIST frameworks.
Develop secure APIs and cloud-native services to transform military healthcare delivery for DHA systems. Build and maintain data pipelines to normalize healthcare data into FHIR and OMOP standards for analytics.
Build, prototype, and refine software and platform solutions for defense-relevant use cases. Translate stakeholder feedback into technical requirements and support technical demonstrations and R&D events.
Lead the design and prototyping of mission-relevant software and platform capabilities within an R&D environment. Translate ambiguous operational needs into working software and represent technical work during customer-facing demos and events.
Build and maintain DevSecOps platforms and Kubernetes clusters using Terraform and Helm charts for US Air Force programs. Ensure all platforms and pipelines comply with DoD cybersecurity policies and industry hardening best practices.
MLOps Engineer — AI/ML Systems & Deployment (TS/SCI Preferred)
Rackner
·
Full Time
·
a month ago
Rackner
Own the end-to-end ML lifecycle by building production-grade pipelines and deploying models into secure, constrained environments. Ensure system reliability through monitoring, auditability, and the creation of sustainable operational documentation.
Design, develop, and deploy advanced machine learning models and training pipelines to support mission-critical systems. Collaborate with cross-functional teams to integrate scalable AI solutions into production environments.
Business Development & Capture Lead (DoD Domain | Remote)
Rackner
·
Full Time
·
3 months ago
Rackner
Lead the full capture lifecycle from discovery through award, including strategy development and proposal execution. Build and maintain strategic relationships with DoD and Air Force decision-makers to influence acquisition requirements.
Platform Engineer (Cloud-Native AI/ML Systems Integration)
Rackner
·
Full Time
·
4 months ago
Rackner
The Platform Engineer will architect and operate Kubernetes-based infrastructure specifically designed to support AI/ML workloads in mission-critical environments, focusing on security and reliability. This involves building and managing containerized deployments, optimizing data pipelines, and developing Infrastructure as Code for repeatable system builds.
