Artificial Intelligence Software Engineer

What you'll do

• Develop and implement end-to-end AI and machine learning solutions to modernize digital engineering capabilities.
• Build full-stack LLM solutions including RAG implementation, model selection, and management via Hugging Face.
• Implement LLM frameworks such as LangChain and LlamaIndex using embedding models and vector databases.
• Utilize inference engines like vLLM and llama.cpp to power AI applications.
• Develop full-stack software components including RESTful APIs, Node.js, JavaScript, and React.
• Build and manage CI/CD pipelines using DevSecOps tools such as GitHub Actions.
• Integrate Model Context Protocol (MCP) to enable seamless model interoperability and context management.
• Perform systems engineering analysis for mission-critical government projects and infrastructure.

What we're looking for

• 2+ years of experience designing, modifying, developing, writing, and implementing software programming applications using methods such as Agile.
• 1+ years of experience working with full-stack LLM solutions, including RAG implementation, model selection, registry management, or frameworks like LangChain or LlamaIndex.
• Experience with full-stack development, including RESTFul APIs, Node.js, JavaScript, or React.
• Knowledge of Agile methodology and DevSecOps tools such as GitHub Actions to build and manage CI/CD pipelines.
• Experience with LLM inference engines.
• Experience with Cursor or AI-assisted coding tools to enhance software or digital engineering development processes.
• Ability to obtain a Secret clearance.
• Master's degree (preferred).
• Industry Certifications such as OCSMP, ASEP, GCP, Azure, AWS, and Security+ (preferred).
• Experience implementing Model Context Protocol (MCP) in software or digital engineering projects (preferred).
• Experience performing systems engineering analysis for government or mission critical systems (preferred).
• Experience with Model-Based Systems Engineering (MBSE) tools such as Cameo, MagicDraw, SparxEA, DOORS, and IBM Rhapsody (preferred).
• Experience with MATLAB, STK, ModelCenter, or TeamCenter (preferred).
• Experience with cloud computing platforms such as AWS, Azure, or GCP (preferred).
• Experience with software product testing and QA/QC (preferred).
• Experience with LLM inference engines such as vLLM and llama.cpp (preferred).