AI Software Engineer
Quick Summary
Architect and implement Retrieval-Augmented Generation (RAG) systems and Large Language Model (LLM) agents to query, summarize,
Education: Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related technical field.
Responsibilities
~2 min read- →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.
Requirements
~1 min read- 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.
- 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).
US Citizenship with an active U.S. Government Secret clearance (or higher) and be eligible to obtain TS/SCI access.
- System Integration: Ability to connect AI models with existing legacy software, APIs, and document management systems seamlessly.
- Problem Solving: Aptitude for turning complex, noisy, multi-dimensional data into intuitive, actionable insights.
- Communication: Ability to communicate technical AI concepts clearly to non-technical stakeholders, scientific subject matter experts, and executive leadership.
We are proud to be an EEO/AA employer Minorities/Women/Veterans/Disabled and other protected categories.
In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.
We are strictly looking for direct, full-time W2 employees. We do not engage with third-party staffing agencies, C2C, or 1099 independent contractors for this role.
Location & Eligibility
Listing Details
- Posted
- August 18, 2026
- First seen
- August 18, 2026
- Last seen
- August 19, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 71%
- Scored at
- August 18, 2026
Signal breakdown
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