AI Implementation Engineer - JobID-0245

About The Role

: Innovative Defense Technologies (IDT), a leading defense technology company, is seeking an AI Implementation Engineer to be part of our Warfare Systems team and based out of our Arlington, VA or Mount Laurel, NJ location. The AI Implementation Engineer will design and deliver engineering-focused AI solutions that move beyond demos into reliable, mission-relevant systems. This role is ideal for an engineer who has extensive experience with commercially available AI tooling/chat, hosting LLM servers and has demonstrated ability to build end-to-end capabilities including MCP integrations, RAG pipelines, tool-using agents, and production-grade AI workflows.

Requirements

S. Security Clearance. This is an on-site position.

Requiring at least 3 days in office, based out of our Arlington, VA location or Mt. Laurel, NJ location.

: Gather, document, and validate technical and functional

from project artifacts, stakeholders, and mission needs to ensure feasibility, completeness, and alignment with operational goals. Collaborate Across Teams: Work closely with engineers, technical leads, and mission stakeholders to integrate AI capabilities into broader software and system architectures. Participate in technical reviews, design discussions, and delivery planning.

Support Technical Quality: Contribute to testing, debugging, and performance optimization of AI-enabled applications, including edge cases involving context management, retrieval failures, tool execution, and orchestration logic. Learn and Apply Emerging Practices: Stay current on advances in LLMs, agent frameworks, orchestration methods, and applied AI engineering practices, and bring that knowledge into practical system design and implementation. Communicate Technical Work: Clearly document architectures, workflows, assumptions, and implementation decisions so that solutions are maintainable, explainable, and transferable across teams.

What You Will Do

: Design and Build AI Solutions for On-Prem systems in Air-Gapped environment: Design and implement end-to-end agentic AI systems that support planning, reasoning, tool use, and multi-step execution in real-world environments. Build modular, testable components that move from prototype to operational capability. Integrate Models and Tools for On-Prem systems in Air-Gapped environment: Develop integrations across LLMs, APIs, data sources, and Model Context Protocol (MCP) interfaces to enable intelligent agents to interact with external systems, retrieve context, and take action safely and reliably.

Develop Retrieval Pipelines for On-Prem systems in Air-Gapped environment: Build and optimize Retrieval-Augmented Generation (RAG) pipelines that connect models to live knowledge sources, structured data, and enterprise content to improve factual grounding, contextual relevance, and response quality. Engineer Conversational and Agentic Interfaces for On-Prem systems in Air-Gapped environment: Create conversational systems and intelligent agents with memory, contextual awareness, adaptive decision-making, and support for multi-turn user and system interactions. Implement and Evaluate AI Workflows for On-Prem systems in Air-Gapped environment: Translate technical objectives into working pipelines, run experiments, evaluate agent behavior, and iterate on prompts, orchestration logic, retrieval quality, and system performance to improve reliability and usability.

Architect local infrastructure to size, config, and optimize local CPU/GPU workloads, utilizing quantization techniques to maximize throughput, etc. Orchestrate disconnected environments, design and maintain offline model update pipelines, local package mirrors, etc.

Who You Are (Required)

: Bachelor’s Degree in Information Technology, Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Physics, Math, or equ