# AI Software Engineer at Dark Wolf Solutions

> United States · Unspecified · Software engineering · open. Source: https://alderhq.app/jobs/greenhouse%3Adarkwolfsolutions%3A7886757003 (read 2026-11-05).

## Facts (observed)

- Company: [Dark Wolf Solutions](https://alderhq.app/companies/dark-wolf-solutions)
- Location text: Chantilly/Herndon, VA; Chantilly, VA
- Where it can be done from (inferred): United States (evidence: "Location: Chantilly/Herndon, VA; Chantilly, VA")
- Posted: 2026-08-18 (79 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/darkwolfsolutions/jobs/7886757003
- Skills listed (inferred): TypeScript, Python, FastAPI, AWS, Azure, Kubernetes, Docker, SQL, PyTorch, TensorFlow, LLMs

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (United States, n 5124): p25 $128k, median $158k, p75 $198k

## Description (the employer's text)

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 workforces.
- 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, TensorFlow, LangChain, LlamaIndex, and modern API frameworks (FastAPI, RESTful APIs).
- Data Pipelines & Databases: Experience working with complex structured and unstructured data sources, SQL, NoSQL, 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 GovCloud, 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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Adarkwolfsolutions%3A7886757003 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.