Artificial Intelligence Full Stack Developer

Job Title: AI Full Stack Developer

Job Category: Information Technology

Time Type: Full time

Minimum Clearance Required to Start: NACI

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

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The Opportunity:
The candidate will be responsible for designing, building, and deploying end-to-end web applications that leverage Artificial Intelligence (AI) and Large Language Models (LLMs) within a secure Department of War (DoW) environment. This requires standard full-stack development skills (frontend UI, backend APIs, and databases) combined with the ability to integrate modern AI pipelines.

** Position is on-site in Dayton, OH**

** Position requires U.S. Citizenship**

Qualifications:

Required: 

· Must be a US Citizenship

· Must be located in the Dayton, OH area
· Backend Development: Advanced proficiency in Python and API frameworks (e.g., FastAPI, Flask) to build the core logic and connect user interfaces to AI models.
· Frontend Development: Experience building clean, intuitive user interfaces using modern frameworks (e.g., React, Vue) or AI-focused UI libraries (e.g., Streamlit) for chat interfaces and search dashboards.
· Data & Database Architecture: Strong experience with relational databases (e.g., PostgreSQL) and Vector Databases (e.g., pgvector, Milvus, Chroma) to manage both application data and AI-searchable embeddings.
· AI Data Integration (RAG): Hands-on experience designing and implementing Retrieval-Augmented Generation (RAG) workflows to allow the AI to securely reference and search internal documents.
· DevOps & Infrastructure: Experience containerizing applications using Docker/Podman and utilizing version control (Git) to package applications for stable deployment.

Desired:
· Secure / Air-Gapped Deployment: Understanding of how to deploy containerized applications in restricted, disconnected, or IL5+ environments without relying on active external cloud connections.
· Open-Source AI Ecosystem: Experience utilizing the Hugging Face library/hub to evaluate, download, and implement open-weight models (e.g., Llama 3, Mistral) locally.
· Local Compute Optimization: Familiarity with model runtime tools (e.g., vLLM, llama.cpp) and quantization techniques (e.g., GGUF) to run large AI models efficiently on standard DoD hardware.
· AI Orchestration Frameworks: Familiarity with frameworks like LangChain or LlamaIndex to accelerate the development of complex AI agent workflows.
· AI Safety & Evaluation: Ability to implement system "guardrails" to prevent off-topic outputs and mitigate AI hallucinations, ensuring secure and accurate mission-support tools.