AI Data Engineer

About the role

MASS Group builds TME®, a mission-critical Manufacturing Operating System designed specifically for defense manufacturers operating in air-gapped, CMMC-compliant environments. Our customers run some of the nation’s most demanding production operations and rely on TME to execute high-stakes production workflows with total confidence. We foster a high-output, low-ego culture grounded in integrity, humility, and transparency, where engineers ship impactful capabilities directly to customers.

As an AI Data Engineer, you will join a high-impact engineering team at a defining moment in our product lifecycle. With the release of TME 9.0, we are introducing a data-agnostic operational layer that transitions defense manufacturing workflows from human-assisted execution to automated operations. In this role, you will balance foundational data modeling and pipeline architecture with practical AI/RAG prototyping (an approximate 50/50 split during your first six months), turning raw, complex industrial data into clean, trustworthy operational intelligence across cloud and air-gapped environments.

Work Location: 100% Remote (Strong preference for candidates based in EST or CST time zones, or located near Boston, MA or Washington, DC). Travel Expectations: 10% to 20% travel per quarter to visit customer manufacturing sites and secure defense installations for on-site deployments and testing.

Responsibilities

• Architect Data Orchestration: Build and extend the core data orchestration layer powering TME 9.0, transitioning customer workflows from human-assisted processes to resilient, automated operations.
• Engineer Robust Pipelines: Turn raw application data from TME and complex legacy customer systems into structured, high-performance, and reliable business models.
• Prototype and Deploy AI Solutions: Develop, evaluate, and productionize practical AI capabilities—including Retrieval-Augmented Generation (RAG) and LLM-driven workflows—to drive operational value.
• Integrate Varied Data Sources: Design and maintain resilient APIs, ETL/ELT pipelines, and integration layers that handle diverse industrial and enterprise data inputs.
• Collaborate with Domain Experts: Partner with manufacturing subject matter experts to implement critical Key Performance Indicators (KPIs), outcome measures, and Statistical Process Control (SPC) calculations.
• Deploy Across Hybrid Infrastructure: Ensure pipeline and AI architecture functions seamlessly across diverse environments, including AWS GovCloud, Azure Government, and localized, on-premises air-gapped deployments.
• Leverage Modern Engineering Practices: Integrate AI tools into your daily engineering workflow to accelerate boilerplate development, scaffolding, and iterative testing.

Requirements

• U.S. Citizenship: Must be a verified U.S. Citizen (required due to handling CMMC-compliant defense manufacturing data and export control regulations).
• Core Data Engineering Competency: Advanced proficiency in SQL, data modeling, relational schema design, and production ETL/ELT pipeline development.
• Software Engineering Foundations: Strong coding