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Job Description
About The Role:
[Innovative Defense Technologies](http://idtus.com/) (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.
Clearance & Location Requirements:
- All applicants must be able to obtain/maintain an active Secret U.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.
### Key Responsibilities
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.
- Scope and Define Requirements: Gather, document, and validate technical and functional requirements 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.
### Skills, Knowledge & Expertise
Who You Are (Required):
- Bachelor’s Degree in Information Technology, Computer Science, Computer Engineering, Electrical Engineering, Systems Engineering, Physics, Math, or equivalent full-time professional experience; Master’s Degree in Engineering or other technical field highly desired
- 5-10+ years of professional experience in software engineering, machine learning engineering, AI engineering, or related technical roles
- Proficiency in Python, including experience with core libraries such as NumPy and Pandas
- Deep hands-on experience with production local inference engines such as vLLM, SGLang, Triton Inference Server, or TensorRT-LLM
- Experience building software with one or more modern AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LangGraph, Semantic Kernel, or AutoGen
- Experience with Linux and hardening (fapolicy/selinux/fips/etc)
- Experience with commercially available AI tooling/chat
- Experience with hosting LLM servers
- Experience with hosting different models (chat/embedding)
- Experience with distributed networking (reverse proxy/load balancing/firewalls/etc)
- Experience with containerization
- Ability to work independently on technical tasks while collaborating effectively in a team environment
- Ability to shift from one project to another in an agile work environment
- Strong leadership capabilities and skills
- Strong documentation skills
- Ability to travel up to 10% of the time, as needed
What Makes You Stand Out:
- Experience hosting LLM servers on local hardware
- Experience with various GPU architectures (NVIDIA preferred)
- Experience with AI Gateways
- Experience with LLM servers and model optimization (VRAM/layers/quantization/fasttensor/kv-cache/parallel/etc)
- Experience with LLM toolcalling
- Experience with RAG
- Experience with vector stores
- Experience with ModelContextProtocol
- Experience with container orchestration
- Experience managing and directing personnel while maintaining cost and schedule targets
- Problem-solving skills with the ability to navigate ambiguous situations
If you see yourself reflected in this role and are excited about the impact you could make, we encourage you to apply! If you know someone who may be a great fit, please feel free to share this opportunity with your network.
Pay Range\: $114,000 - $184,000 or $135,000 - $231,000
\Pursuant to New Jersey [Senate Bill 2310](https://www.njleg.state.nj.us/bill-search/2024/S2310) IDT is required to disclose the “pay scale” or “pay range” associated with a job posting. Notably, however, this amount may not be reflective of actual compensation that may be earned as pay is dependent on a candidate’s experience, skills, and education. The posted range does not include bonuses, commissions, tips, or other benefits. Click [here](https://njleg.state.nj.us/bill-search/2024/S2310/bill-text?f=S2500&n=2310_I1) for additional information about Senate Bill 2310. IDT is often looking to place multiple candidates at various levels. Therefore, more than one pay range has been included, commensurate with experience.
### Job Benefits
Why Work at Innovative Defense Technologies (IDT):
IDT is a growing company with a vibrant, entrepreneurial culture. We are headquartered in Arlington, VA with additional offices in Fall River, MA; Mount Laurel, NJ; and San Diego, CA. At each location, our employees work together in a modern, snack-filled, and social office space, designing innovative solutions for our defense industry customers. We offer employees competitive pay and benefits including:
- Generous [benefits](https://idtus.com/careers/employee-benefits/) package
- Competitive PTO
- Paid holidays
- 401(k) with immediate vesting and matching
- 9/80 optional schedule (2nd and 4th Friday off every month)
- Tuition Assistance Reimbursement Program
- Professional Development Resources
- Pre-Tax Commuter Benefits
- Organization-Wide Monthly Tech Connect Events
- Annual Employee Recognition Awards
- Regular Social Events and Catered Lunches
EEO Statement:
IDT is an Equal Opportunity employer.
Key Responsibilities
Design and build end-to-end agentic AI systems for on-prem, air-gapped environments.
Integrate LLMs, APIs, and Model Context Protocol interfaces to enable intelligent agent interactions.
Develop and optimize Retrieval-Augmented Generation (RAG) pipelines for factual grounding.
Engineer conversational systems and intelligent agents with memory and adaptive decision-making.
Implement and evaluate AI workflows, including prompt optimization and system performance testing.
Architect local infrastructure to size and optimize CPU/GPU workloads using quantization techniques.
Orchestrate disconnected environments and maintain offline model update pipelines.
Gather and validate technical and functional requirements from stakeholders.
Collaborate with engineers and technical leads to integrate AI capabilities into broader architectures.
Contribute to testing, debugging, and performance optimization of AI-enabled applications.
Document architectures, workflows, and implementation decisions for maintainability.
Requirements
Bachelor’s Degree in Information Technology
Computer Science
Computer Engineering
Electrical Engineering
Systems Engineering
Physics
Math
or equivalent full-time professional experience
Skills Required
PythonNumPyPandasvLLMSGLangTriton Inference ServerTensorRT-LLMPyTorchTensorFlowLangChainLangGraphSemantic KernelAutoGenLinuxfapolicyselinuxfipsLLM serversDistributed networkingReverse proxyLoad balancingFirewallsContainerizationAgileAbility to work independentlyCollaborationLeadershipDocumentationCommunicationNVIDIA GPU architecturesAI GatewaysLLM server hosting on local hardwareModel optimization (VRAM, layers, quantization, fasttensor, kv-cache, parallel)LLM toolcallingVector storesContainer orchestrationPersonnel managementProblem-solvingNavigating ambiguous situations
Benefits
Generous benefits package
Competitive PTO
Paid holidays
401(k) with immediate vesting and matching
9/80 optional schedule
Tuition Assistance Reimbursement Program
Professional Development Resources
Pre-Tax Commuter Benefits
Organization-Wide Monthly Tech Connect Events
Annual Employee Recognition Awards
Regular Social Events and Catered Lunches
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