AI Software Engineer

Dark Wolf
constructs and deploys data management and analytics solutions for the defense and intelligence communities. We’re proud to boast a world-class engineering team that thrives on rolling up their sleeves to solve your mission’s biggest challenges.

Dark Wolf is seeking a highly skilled Senior AI Engineer to architect, build, and deploy advanced, secure AI-driven solutions supporting federal and defense enterprises. In this role, you will tackle enterprise data fragmentation by designing automated data ingestion pipelines, Retrieval-Augmented Generation (RAG) architectures, and predictive analytics tools.

You will directly address critical operational areas including HR workforce analytics, enterprise workflow automation, program management analytics, and automated scientific literature discovery.

Key Responsibilities:

• Architect and implement Retrieval-Augmented Generation (RAG) systems and Large Language Model (LLM) agents to query, summarize, and synthesize insights across large volumes of structured and unstructured data.
• Build semantic search engines capable of integrating internal legacy databases, data lakes, open-source repositories, and subscription-based scientific literature via APIs.
• Implement natural language translation, automated document classification, and multi-document summarization to augment science and technology gap analysis.
• Develop intelligent chatbots and virtual agents to deliver automated, role-based recommendations, career path mapping, and skills gap analysis for enterprise work forces.
• Build NLP-driven tasking models to ingest natural language inquiries, query underlying enterprise data sources, and draft contextual responses with audit trails for records management compliance.
• Design ML algorithms (including anomaly detection, predictive modeling, and causal inference) to identify project risks, optimize resource allocation, and forecast financial/technical shifts.
• Collaborate with UI/UX and data engineers to build interactive, role-based dashboards enabling natural language querying and drill-down analytics for leadership decision-making.
• Design automated ingestion and ETL/ELT pipelines using NLP and pattern recognition to transform disparate data formats into a standardized, unified Data Fabric schema.
• Implement robust Explainable AI (XAI) techniques to ensure transparency and trustworthiness of model recommendations.
• Ensure all AI models, APIs, and data storage solutions strictly adhere to DoD security regulations (e.g., NIST, FedRAMP, Risk Management Framework) across multiple classification levels.

Required Qualifications:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field.
• Experience: 5+ years of experience engineering production-grade AI/ML systems (or 3+ years with a Master's/Ph.D.).
• NLP & LLMs: Hands-on experience fine-tuning, evaluating, and deploying open-source and proprietary LLMs, embedding models, and vector databases (e.g., Pinecone, Milvus, Qdrant, FAISS).
• Programming & Frameworks: Proficiency in Python, PyTorch, Tensor Flow, Lang Chain, Llama Index, and modern API frameworks (FastAPI, RESTful APIs).
• Data Pipelines & Databases: Experience working with complex structured and unstructured data sources, SQL, No
  
  SQL, graph databases, and data lakes.
• Security Clearance: Must hold an active U.S. Government Secret clearance (or higher) and be eligible to obtain TS/SCI access.

Preferred Qualifications:

• Experience deploying AI applications within DoD, Air Force, or Federal agency environments (CAC/PKI integration, IL4/IL5/IL6 cloud environments).
• Proven track record building XAI (Explainable AI) architectures for leadership decision support.
• Background in developing AI solutions for HR systems, workflow management software, or scientific/academic literature indexing.
• Experience with cloud platforms (AWS Gov Cloud, Azure Government) and containerized deployment technologies (Docker, Kubernetes).

Core Competencies:

• System Integration: Ability to connect AI models with existing legacy software, APIs, and document management systems seamlessly.
• Problem Solving: Aptitude for turning…