AI Data Systems Engineer

JCTM, LLC•Quantico, VA

1d•$123,000 - $135,000

About The Position

The data foundation behind AI-enabled warfighting capabilities is critical to aligning our military forces for the future operating environment. As an AI Data Systems Engineer with JCTM, you will support the Marine Corps Warfighting Lab by owning the data foundation for AI Branch initiatives. This position requires hands-on data engineering depth and the ability to assess how data is collected, moved, stored, secured, and structured to support AI capabilities across cloud, on-premise, and tactical edge environments. At JCTM, we value knowledge, experience, integrity, and commitment. Joining our team means becoming part of an organization that empowers individuals, prioritizes ethical practices, and fosters a culture of collaboration and growth. Expand your expertise by working with cutting-edge AI data systems, tactical edge architectures, sensor data pipelines, and advanced data governance methodologies, optimizing their application in a dynamic environment. Collaborate with a diverse team of technical and functional experts, gaining practical experience with advanced tools, technologies, and strategic-level implementations. You will have opportunities to grow your career and contribute to the company's strategic goals, supported by mentorship and a collaborative work environment.

Requirements

Bachelor's degree in Computer Science, Data Engineering, Computer Engineering, or a related technical field
5+ years of experience in data engineering including hands-on ETL pipeline design, data pipeline architecture, and large-scale data systems
Strong understanding of data storage systems, database design, and data modeling across structured and unstructured data
Demonstrated ability to assess third-party data architectures and technical claims distinguishing sound design from marketing representation
Understanding of data considerations specific to edge and disconnected, degraded, intermittent, or limited environments
Strong understanding of data governance, security, and data rights principles including DFARS data rights considerations
Experience advising technical and non-technical stakeholders on data practice changes
Excellent written and verbal communication skills including the ability to clearly articulate ideas for executive level consumption
Ability to use prior experience and knowledge to address new situations especially during interactions with clients
US Citizenship

Nice To Haves

Active TS/SCI Security Clearance or ability to obtain TS/SCI eligibility
Master's degree in a relevant technical field
Experience with sensor data including imagery, video, or signals in a defense or intelligence context
Experience evaluating or building data pipelines for machine learning training and inference distinct from data science or analytics work
Prior military experience particularly within the Marine Corps
Familiarity with Marine Corps data systems, MAGTF operations, and relevant DoD data policy
Familiarity with MOSA-related data interoperability considerations

Responsibilities

Design, assess, and advise on ETL pipelines and data architectures supporting AI Branch projects, including Automatic Target Recognition, Autonomous Vehicle Orchestration, and AI-enabled command and control efforts.
Evaluate data storage strategies across cloud, on-premise, and disconnected, degraded, intermittent, or limited tactical edge environments, including tradeoffs in latency, resilience, and bandwidth.
Define and enforce data quality, typing, taxonomy, labeling, and formatting standards for datasets used in AI training, testing, and inference.
Assess vendor-proposed data architectures, data rights postures, and data handling claims as part of gated technical evaluations; identify gaps between claimed and demonstrated data maturity.
Advise AI Branch leadership and requirements owners on data practices the Marine Corps needs to adopt for AI capabilities to be viable at scale.
Analyze how candidate AI systems ingest, process, move, secure, and produce data, identifying risks, bottlenecks, and integration challenges.
Support data governance, security, and data rights reviews in coordination with cybersecurity, legal, and contracting stakeholders.
Partner with deployment and infrastructure teams to ensure data pipelines are compatible with deployment architecture, system boundaries, and operational constraints.
Support experiments, wargames, and exercises by ensuring collected data is well-structured, accessible, secure, and usable for downstream evaluation.
Prepare technical assessments, briefings, and documentation on data architecture, data maturity, and data solution evaluations for leadership and transition partners.
Travel as required (estimated up to 10%) to support data collection, integration, and experimentation events.