AI Data Systems Engineer

JCTM

$110K — $130K *
Aerospace & Defense
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Computer Science, Data Engineering, Computer Engineering, or related field
  • 5+ years of experience in data engineering, including ETL pipeline design and large-scale data systems
  • Strong understanding of data storage, database design, and modeling for structured and unstructured data
  • Ability to evaluate third-party data architectures and differentiate between marketing claims and sound design
  • Knowledge of data governance, security, and data rights principles, including DFARS considerations
  • Capacity to communicate complex ideas to technical and non-technical stakeholders
  • US Citizenship required

Responsibilities

  • Design and assess ETL pipelines and data architectures for AI Branch projects
  • Evaluate data storage strategies for cloud, on-premise, and tactical environments
  • Define and enforce data quality standards for datasets used in AI
  • Assess vendor data architectures and identify maturity gaps
  • Advise AI Branch leadership on data practices for scalable AI capabilities
  • Analyze data ingestion and processing of candidate AI systems
  • Support data governance, security, and rights reviews in collaboration with various stakeholders
  • Ensure compatibility of data pipelines with deployment architecture
  • Assist in experiments and exercises to ensure usability of structured data
  • Prepare technical documentation and assessments for leadership

Benefits

  • Opportunity to work with cutting-edge AI data systems and technologies
  • Gain practical experience with advanced tools and strategic implementations
  • Grow your career with support from mentorship and a collaborative environment
  • Work on impactful projects that support military capabilities
  • Potential for travel to support data collection and experiments
Full Job Description
The Challenge:

The data foundation behind AI-enabled warfighting capabilities is critical to aligning our military forces for the future operating environment. What if you could use your data engineering knowledge and technical judgment to help the Marine Corps evaluate, structure, and scale the data systems required for operational AI?

Challenging Projects:

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.

Key Responsibilities:
  • Data Architecture and Pipeline Design: 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.
  • Storage and Edge Data Strategy: Evaluate data storage strategies across cloud, on-premise, and disconnected, degraded, intermittent, or limited tactical edge environments, including tradeoffs in latency, resilience, and bandwidth.
  • Data Quality and Standards: Define and enforce data quality, typing, taxonomy, labeling, and formatting standards for datasets used in AI training, testing, and inference.
  • Vendor Technical Evaluation: 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.
  • Marine Corps Data Advising: Advise AI Branch leadership and requirements owners on data practices the Marine Corps needs to adopt for AI capabilities to be viable at scale.
  • Data Flow Analysis: Analyze how candidate AI systems ingest, process, move, secure, and produce data, identifying risks, bottlenecks, and integration challenges.
  • Governance and Data Rights: Support data governance, security, and data rights reviews in coordination with cybersecurity, legal, and contracting stakeholders.
  • Deployment Integration: Partner with deployment and infrastructure teams to ensure data pipelines are compatible with deployment architecture, system boundaries, and operational constraints.
  • Experimentation Support: Support experiments, wargames, and exercises by ensuring collected data is well-structured, accessible, secure, and usable for downstream evaluation.
  • Technical Documentation: Prepare technical assessments, briefings, and documentation on data architecture, data maturity, and data solution evaluations for leadership and transition partners.
  • Travel Support: Travel as required (estimated up to 10%) to support data collection, integration, and experimentation events.

State-of-the-Art Technology:

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.

New Skills:

Collaborate with a diverse team of technical and functional experts gaining practical experience with advanced tools technologies and strategic-level implementations.

Room to Grow:

You will have opportunities to grow your career and contribute to the company's strategic goals supported by mentorship and a collaborative work environment.

You Have:
  • 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

Clearance:

Applicants selected will be subject to a security investigation and must meet eligibility requirements for access to classified information; TS/SCI clearance is required.

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