Software Engineer - AI (Top Secret Clearance Required)
On-siteAlexandria, Virginia, United States
Job Summary
Design and implement AI architectures for operational monitoring, coding improvements, and secure dashboard tooling. Lead the development of AI capabilities across multiple operational cloud environments, including AWS resiliency, recovery procedures, and automated failover orchestration. Enhance software development workflows, quality metrics, and dashboards using AI while deploying custom code, COTS, and GOTS solutions with a geospatial focus. Collaborate with technical leadership and external stakeholders to optimize agent and customer experiences through secure, automated cloud initiatives. Apply broad systems engineering lifecycle experience to cloud architectural design, CI/CD pipeline management, and infrastructure automation using Python, Terraform, and AWS CloudFormation.
Required Qualifications
- Active Top Secret (TS) security clearance with the ability to obtain SCI with CI Polygraph
- DoD 8570 compliant certification (IAT Level II/III, e.g., Security+ or higher)
- Bachelor's degree in Computer Science, Engineering, or a related field
- Subject matter expertise across a range of AI technologies
- Proficient in Python
- Designing and implementing distributed, cloud based solutions (Cloud, SOA, Web Services)
- Experience with Cloud/PaaS environments
- CI/CD and DevOps tooling such as GitLab and Jenkins
- Infrastructure as Code using AWS CloudFormation and Terraform
- Database development, for example with PostgreSQL
Desired Qualifications
- Windows and Linux system administration
- Knowledge of SDLC and Agile best practices, including Scrum and Kanban
- Virtualization, networking, and operating system experience
- Infrastructure monitoring with Zabbix
- Security compliance scanning with ACAS
- Team collaboration tools such as Jira, Confluence, and RocketChat
- Understanding of the SFH organization and Sea data and mission
- Experience with NGA cloud based architecture
- Experience with IC Cloud architecture implementation methodologies
- Experience building and maintaining CI/CD pipelines and projects
- AWS certifications such as Solutions Architect, Developer, or Machine Learning
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