Remote AI Data Engineer — RAG & Pipelines for Defense

SG2 Recruiting; Henderson (NV); Remote; USD 150,000 - 175,000; Full time

Benefits offered by this job

Health, dental, and vision coverage

Retirement savings plans

Paid time off

Professional development support

Job summary

MASS Group is seeking an AI Data Engineer to join a high-impact engineering team. You will balance data modeling and pipeline architecture with practical AI prototyping (RAG/LLM) across cloud and air-gapped environments.

Responsibilities include building data orchestration layers, transforming complex industrial data into actionable insights, and deploying AI solutions in hybrid infrastructure for defense manufacturing contexts.

Qualifications

• Advanced proficiency in SQL and data modeling for production ETL/ELT pipelines.
• Strong coding background in Python with RESTful API integrations.
• Experience prototyping AI solutions (RAG, LLM) and enterprise-scale architectures.
• Hybrid deployment across cloud and air-gapped environments.

Responsibilities

• Architect Data Orchestration: build/extend core data layer powering TME 9.0 for automated ops.
• Engineer Robust Pipelines: transform raw data into structured, high-performance models.
• Prototype and Deploy AI Solutions: develop, evaluate, and productionize AI capabilities (RAG/LLM).
• Integrate Varied Data Sources: design APIs and ETL/ELT pipelines for diverse inputs.
• Collaborate with Domain Experts: define KPIs and SPC calculations with manufacturing teams.
• Deploy Across Hybrid Infrastructure: ensure AI/PIPELINE works across AWS GovCloud, Azure Gov, on-prem.
• Leverage Modern Engineering Practices: accelerate boilerplate development and testing.

Skills

SQL

Data modeling

ETL/ELT pipelines

Python

RESTful APIs

AI prototyping

RAG

LLM integrations

Hybrid deployment

Tools

AWS GovCloud

Azure Government

On-premises servers

Job description

MASS Group is seeking an AI Data Engineer to join a high-impact engineering team. You will balance data modeling and pipeline architecture with practical AI prototyping (RAG/LLM) across cloud and air-gapped environments.

Responsibilities include building data orchestration layers, transforming complex industrial data into actionable insights, and deploying AI solutions in hybrid infrastructure for defense manufacturing contexts.