Applied AI Engineer
Core
Build and ship language-model-powered systems to strengthen mission-critical cyber capabilities for U.S. national security.
Role type
Applied AI Engineer (LLM Systems)
Builds
Production LLM inference and retrieval systems for cyber operations
Domain
National Security / Cyber Operations / AI
Deliverable
production ML models
Required skills
Python, deep learning (PyTorch/TensorFlow/JAX), LLM post-training (SFT/RLHF/DPO), dataset curation, vector databases, evaluation metrics, orchestration frameworks (LangChain/LangGraph)
Preferred skills
distributed training, model quantization, LLMOps practices
Technologies
PyTorch, TensorFlow, JAX, vLLM, TensorRT, ONNX, pgvector, ChromaDB, Pinecone, Milvus, Weaviate, Pydantic-AI, LangChain, LangGraph, CrewAI, Docker, Kubernetes, AWS, GCP, Azure
Responsibilities
Create and maintain training/evaluation datasets; Fine-tune language models; Implement post-training and alignment approaches; Build RAG systems; Develop model serving infrastructure; Design evaluation frameworks; Integrate AI capabilities into workflows; Produce technical documentation
Seniority
Mid-Senior, hands-on IC
