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Explainable Ai Jobs in Virginia (NOW HIRING)

AI Software Engineer

Chantilly, VA ยท Remote

$120K - $160K/yr

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 ...

AI Software Engineer

Herndon, VA ยท On-site

$120K - $160K/yr

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 ...

AI Software Engineer

Herndon, VA ยท On-site

$120K - $160K/yr

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 ...

AI Software Engineer

Chantilly, VA ยท On-site

$120K - $160K/yr

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 ...

AI Software Engineer

Chantilly, VA ยท Remote

$120K - $160K/yr

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 ...

Design and implement production AI/ML systems compliant with federal, DHS, and ICE governance requirements Develop explainable and auditable AI solutions with integrated human-in-the-loop oversight ...

Design and implement production AI/ML systems compliant with federal, DHS, and ICE governance requirements Develop explainable and auditable AI solutions with integrated human-in-the-loop oversight ...

Senior AI Engineer

Alexandria, VA ยท Hybrid

$131K - $237K/yr

Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. * Contribute to the integration of AI ...

Sr AI/ML Engineer

Herndon, VA ยท On-site

$107K - $147K/yr

Familiarity with explainable AI (XAI) techniques for safety-critical environments. * Hands-on experience with reinforcement learning and real-time systems applicable to MPC. Qualifications We Prefer:

Senior AI Engineer

Alexandria, VA ยท On-site

$131K - $237K/yr

Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. * Contribute to the integration of AI ...

AI/ML Subject Matter Expert

Vienna, VA ยท On-site

$195K - $210K/yr

Ensure code security, model governance, and adherence to Responsible and Explainable AI practices * Regularly recommend and report on industry trends and solutions to meet evolving client needs ...

Staff Solutions Architect (U.S. Government)

Reston, VA ยท On-site

$65.50 - $86.25/hr

Seekr is building trusted, explainable AI solutions for mission-critical environments. We are seeking a Solutions Architect to help U.S. Government customers understand and adopt our AI platform and ...

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Showing results 1-20

Explainable Ai information

What is Explainable AI?

Explainable AI (XAI) refers to methods and techniques in artificial intelligence that make the results of AI models understandable and interpretable by humans. XAI aims to provide transparency into how AI systems make decisions, helping users trust and effectively manage AI applications. This is especially important in fields like healthcare, finance, and law, where understanding the reasoning behind AI-driven outcomes can be crucial for accountability and compliance. By making AI more transparent, XAI also helps identify and address biases or errors in AI systems.

What are the key skills and qualifications needed to thrive as an Explainable AI specialist?

To thrive as an Explainable AI specialist, you need a strong background in machine learning, data science, and statistics, typically with an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and libraries like LIME or SHAP, as well as experience in model interpretability tools, is essential. Strong analytical thinking, effective communication, and the ability to translate complex technical concepts for non-technical stakeholders are crucial soft skills. These capabilities ensure that AI models are transparent, trustworthy, and can be responsibly integrated into decision-making processes.

What are some of the typical challenges faced when working in Explainable AI and how do professionals address them?

Professionals in Explainable AI often encounter challenges such as balancing model accuracy with interpretability, translating complex model outputs into understandable insights for non-technical stakeholders, and ensuring transparency without compromising sensitive data. Addressing these issues typically involves using specialized tools and frameworks for visualization, collaborating closely with data scientists, domain experts, and business teams, and staying updated on the latest research in model interpretability. Continuous learning and open communication are key to overcoming these challenges and delivering AI solutions that are both effective and trustworthy.

What is the difference between Explainable Ai vs Data Scientist?

AspectExplainable AiData Scientist
CredentialsTypically requires knowledge of AI, machine learning, and data analysis; certifications like AI or ML courses are commonRequires degrees in computer science, statistics, or related fields; certifications in data analysis or machine learning are beneficial
Work EnvironmentWorks within AI development teams, focusing on model transparency and interpretabilityWorks across data analysis, model building, and business insights, often in research or corporate settings
Industry UsageUsed in AI development, healthcare, finance, and any field requiring transparent AI modelsApplied in tech, finance, healthcare, and research for data-driven decision making

Explainable Ai focuses on making AI models transparent and understandable, ensuring trust and compliance. Data Scientists develop and analyze models, often working with complex data. While both roles involve AI and data, Explainable Ai specialists emphasize interpretability, whereas Data Scientists focus on model creation and insights.

What are popular job titles related to Explainable Ai jobs in Virginia?

For Explainable Ai jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Explainable Ai jobs in Virginia look for?

The top searched job categories for Explainable Ai jobs in Virginia are:

What cities in Virginia are hiring for Explainable Ai jobs?

Cities in Virginia with the most Explainable Ai job openings:

Infographic showing various Explainable Ai job openings in Virginia as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution.

AI Software Engineer

Chantilly, VA โ€ข Remote

Dark Wolf Solutions
IT Servicesย โ€ขย 51 - 200 employees

$120K - $160K/yr

Full-time

Posted 25 days ago


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 scientific literature via APIs.

  • Design automated ingestion and ETL/ELT pipelines using NLP and pattern recognition to transform disparate data formats into a standardized, unified Data Fabric schema.


Job description

Dark Wolfย 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 ย  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.
  • 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.


Position Clearance Requirement:ย 

US Citizenship with an active U.S. Government Secret clearance (or higher) and be eligible to obtain TS/SCI access.


Location:
ย  Chantilly/Herndon, VA.ย 

Target Salary Range: $120,000.00 - $160,000.00 (Commensurate with specialized expertise and technical skillset).


Equal Opportunity Employer:

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, confirm US Citizenship, and complete the required employment eligibility verification 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.