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Dark Wolf Solutions

AI Software Engineer

Chantilly/Herndon, VA$120k–$160kmidAdded today

About this role

Dark Wolf seeks a Senior AI Engineer to design and deploy advanced AI solutions for defense and intelligence agencies, focusing on RAG systems, LLM agents, NLP pipelines, and predictive analytics. You'll architect end-to-end data integration and intelligence platforms while ensuring compliance with DoD security standards.

What you'll do

  • Architect and deploy RAG systems and LLM agents for querying and synthesizing insights across structured and unstructured data
  • Build semantic search engines integrating legacy databases, data lakes, and scientific literature APIs
  • Develop NLP-driven models for document classification, multi-document summarization, and natural language translation
  • Design ML algorithms for anomaly detection, predictive modeling, and causal inference to optimize resource allocation
  • Implement automated ETL/ELT pipelines with NLP and pattern recognition to standardize disparate data formats
  • Ensure all AI models and data solutions comply with DoD security regulations (NIST, FedRAMP, RMF) across classification levels

What they're looking for

  • LLM fine-tuning and deployment (open-source and proprietary models)
  • Vector databases (Pinecone, Milvus, Qdrant, FAISS)
  • Python, PyTorch, TensorFlow, LangChain, LlamaIndex
  • API frameworks (FastAPI, RESTful APIs)
  • SQL, NoSQL, graph databases, and data lake management
  • Explainable AI (XAI) and model interpretability
  • DoD security standards (NIST, FedRAMP, Risk Management Framework)
  • Cloud platforms (AWS GovCloud, Azure Government, Docker, Kubernetes)
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Dark Wolf Solutions

Dark Wolf Solutions builds DevSecOps platforms, integration systems, and data analytics solutions for defense and intelligence customers, with a focus on DoD and Space Force operations. The company is hiring DevOps engineers, full-stack software engineers, systems engineers, and data engineers to support cloud infrastructure, platform development, radar systems, and mission-critical defense applications.

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Likely interview questions

  • Describe a production RAG system you've built—how did you select your vector database and optimize retrieval quality?
  • How have you ensured explainability and auditability in AI models for compliance-critical applications?
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