SMX is seeking a Data Engineer (AI) Senior Engineer to contribute to the development and sustainment of data pipelines and data services that enable AI/ML capabilities within Army Intelligence mission environments.
Requirements
- Hands-on experience with data engineering or large-scale data processing.
- Experience with programming and/or scripting languages (e.g., Python, SQL, Bash).
- Familiarity with cloud platforms, data storage systems, and workflow orchestration tools.
- Understanding of containerization and CI/CD principles.
- Security+ or related DoDD 8140-relevant certification.
- Familiarity with military operations, intelligence workflows, and digital platforms.
- Ability to work within the constraints of military security and compliance standards.
Responsibilities
- Build, maintain, and optimize ETL/ELT pipelines that supply structured and unstructured data to AI/ML workflows.
- Implement data ingestion, cleansing, transformation, normalization, and feature preparation steps according to established methods.
- Ensure pipelines are reliable, repeatable, and well-documented.
- Perform data profiling, validation, and integrity checks to ensure high-quality inputs to AI/ML models.
- Monitor data pipeline performance and data flow health; document and escalate issues to senior engineers.
- Employ Agile methodologies for project management.
- Manage deployment pipelines, containerization, and CI/CD workflows for AI services in the cloud to ensure reproducible data operations.
Other
- Active TS security clearance and eligible for SCI and NATO read-on prior to starting work
- Meet all requirements to receive a privileged user account on a TS/SCI information system
- Master’s degree in Computer Science, Data Science, Engineering, or a related technical field and 3+ years of experience
- Bachelor’s Degree and in Computer Science, Data Science, Engineering, or a related technical field and 7+ years of experience
- Ability to work closely with model developers, analysis, and platform engineers to understand data requirements and operational context
