Minimum Qualifications:
- Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or related technical field and 5 years of related experience. Additional 4 years of equivalent professional experience will be considered in lieu of the degree requirement.
- Minimum of 3 years of experience in software development or data science, with at least 2 years focused specifically on generative AI, LLM applications, or natural language processing (NLP).
- Demonstrated hands-on expertise with foundation models (GPT-4, Claude, Gemini, Llama, Mistral) including prompt engineering, few-shot learning, fine-tuning, and API integration.
- Strong proficiency in Python with experience in LLM frameworks and libraries (LangChain, LlamaIndex, Hugging Face Transformers, OpenAI API, Anthropic API).
- Experience implementing retrieval-augmented generation (RAG) systems including vector databases (Pinecone, Weaviate, ChromaDB, pgvector), embedding models, and semantic search.
- Familiarity with cloud platforms (AWS, Microsoft Azure) and experience deploying AI/ML models in production environments, including Azure OpenAI Service.
- Understanding of AI safety, responsible AI principles, and techniques for mitigating hallucinations, bias, and prompt injection vulnerabilities.
- Experience with version control (Git), CI/CD pipelines, and collaborative development practices in DevSecOps environments.
- U.S citizenship required.
- Active Secret clearance required with eligibility for a final TS/SCI security clearance.
- Valid U.S. passport required for potential OCONUS travel to customer sites.
Preferred Qualifications:
- Master's degree preferred.
- Experience with agentic AI architectures, multi-agent systems, autonomous AI workflows, and tool-use capabilities in LLM applications.
- Hands-on experience with model fine-tuning, RLHF (Reinforcement Learning from Human Feedback), DPO, or parameter-efficient fine-tuning methods (LoRA, QLoRA).
- Familiarity with multimodal AI models (vision-language models, image generation, audio/video processing) and their application to defense use cases.
- Experience with IRIS platform, OMEGA systems, or similar defense/intelligence operational platforms.
- Background in information operations, PSYOP, influence analysis, or supporting Combatant Commands (COCOMs) in technical capacity.
- Knowledge of MLOps practices including model monitoring, A/B testing, performance optimization, and LLM evaluation frameworks (RAGAS, DeepEval).
- Experience with synthetic data generation, simulation environments, or Monte Carlo methods for outcome prediction.
- Understanding of geospatial data formats (GeoJSON, KML) and visualization libraries (Plotly, D3.js) for operational applications.
- Strong communication skills with ability to explain complex AI concepts to non-technical stakeholders and support customer demonstrations.
- Relevant certifications such as AWS Machine Learning Specialty, Azure AI Engineer, Google Cloud Professional ML Engineer, or DeepLearning.AI certifications.
Key Technologies & Platforms:
GPT-4, Claude, Gemini, Azure OpenAI Service, LangChain, LlamaIndex, Hugging Face Transformers, Python, Pinecone, ChromaDB, Weaviate, pgvector, AWS, Microsoft Azure, Docker, Kubernetes, REST APIs, GeoJSON, JSON Schema, Plotly, D3.js, IRIS Platform, Maven, C2IE, OMEGA, FedRAMP IL2-4