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Maintain and enhance a full-stack application supporting intelligence missions. Design and implement data layer, application code, user interface, APIs, and integrations. Build, test (unit and integration), containerize, and deploy services on AWS. Work with lead developer and mission partners to deliver production-ready capabilities.

Design, implement, and maintain platform infrastructure to support applications and services. Manage Kubernetes clusters, Helm charts, configuration management (Ansible/Puppet), RedHat Linux administration, CI/CD pipelines, container environments, and AWS IAM. Ensure reliability, scalability, security, cost-efficiency, and support mission partners. Work collaboratively to troubleshoot and drive continuous improvement. Active TS/SCI with Poly required.

The role involves analyzing Synthetic Aperture Radar imagery, curating data for Machine Learning, and recommending strategies based on sensor characteristics.

Lead SAR exploitation and imagery science initiatives, analyze SAR characteristics, develop algorithms and processing methods, and communicate findings.

Provide high-level support to the General Counsel and legal team, manage workflows, assist with corporate governance, prepare legal documents, and ensure confidentiality.

Design, build, and lead full-stack development of a command-and-control platform. Work with mission partners to convert requirements into features, architect large-scale data pipelines, implement high-performance backend services and React/Django frontends, enforce quality and CI/CD practices, mentor developers, and produce technical documentation and CONOPS.

The Data Scientist will create and deliver analytic processes and data solutions while coordinating with clients to address data-related issues. Responsibilities include designing data architecture, building ETL pipelines, integrating APIs, conducting impact analysis, and preprocessing geospatial data.

Manage, structure, and optimize geospatial and enterprise data to support GEOINT operations. Design and normalize RDBMS schemas, maintain enterprise geodatabases (SDE), enforce metadata and extraction standards, and collaborate with analysts and engineers to improve data workflows, governance, and usability across analytic environments.

Develop and prototype cloud-native data science and machine-learning solutions for behavioral, geo-temporal, social, and content analysis. Build scalable processing pipelines, integrate distributed storage and databases, perform requirements analysis, and advance machine learning research for operational mission problems in a multi-tenant environment.

Join a Chantilly, VA on-site team to develop middleware and backend services. You'll build and optimize Solr/Elasticsearch search infrastructure, work in big data environments (Hadoop/PySpark/Spark/HBase), deliver production-quality Java backend code, and participate in code reviews and testing. Active TS/SCI with Polygraph required.