Sr. Software Engineer I (6521)

MetroStar is a company dedicated to delivering exceptional technology services to the federal government. As a Sr. Software Engineer I, you will work with AI team members to operationalize data pipelines and ML tasks, while providing architectural leadership and technical support to ensure security requirements are met.

Responsibilities:

• You'll work with AI team members to operationalize data pipelines and ML tasks
• You'll provide day-to-day support of deploying Python-native ML pipelines
• You'll support architectural leadership, technical support, and advisement services to ensure identity management system technologies are integrated and meeting the appropriate security requirements
• You’ll support leadership who engage with senior level executives at a public facing Federal agency and provide subject matter expertise in security architecture and other key domain areas

Requirements:

• A minimum of 4 years of experience in the Information Technology field, focusing on development projects using DevSecOps and AWS cloud environments
• A bachelor's degree in Computer Science, Information Technology Management or Engineering, or other comparable degree; or equivalent experience in lieu of degree
• Active Secret or T1 background investigation
• At least 3 years of specific experience with full stack engineering (defined as proficient in database development/integration as well as server and client application development/integration), including at least 3 years of experience deploying production enterprise applications in AWS
• Experience designing, developing, and deploying applications leveraging AWS cloud services in IL6+ classified environments
• Experience in large-scale, high-performance enterprise big data application deployment and solution architecture on complex heterogeneous environments in AWS
• Experience with automation and engineering tasks, implementation, data, infrastructure/operations, and security engineer tasks in cloud environments
• The ability to perform, but not limited to, automation and engineering tasks, testing, implementation, data, AI/ML, infrastructure/operations, and security engineer tasks in cloud environments