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Knowledge Engineer Jobs in Virginia (NOW HIRING)

Knowledge Manager

Mclean, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

Experience with information architecture, scripting, programming, software applications, and ... Knowledge of planning and coordinating the life cycle of organizational data, including record ...

Knowledge Manager

Fairfax, VA · On-site

$55K - $126K/yr

Knowledge Manager The Opportunity: The right interface can make a site easy to use, encourage early ... We're looking for you, a web developer who will use equal parts skill and vision to create an ...

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Knowledge Engineer information

See Virginia salary details

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$47

$72

How much do knowledge engineer jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for knowledge engineer in Virginia is $47.20, according to ZipRecruiter salary data. Most workers in this role earn between $38.85 and $57.21 per hour, depending on experience, location, and employer.

Which 5 jobs will survive AI?

Knowledge engineers design and refine AI systems by creating data models and algorithms, making their roles less susceptible to automation. Jobs that require complex problem-solving, emotional intelligence, creativity, and specialized expertise—such as healthcare professionals, educators, software developers, researchers, and skilled tradespeople—are more likely to endure AI advancements. Continuous learning and adapting to new tools are essential for these roles to remain relevant.

What are some common challenges Knowledge Engineers face when collaborating with subject matter experts (SMEs)?

Knowledge Engineers often work closely with subject matter experts to extract and formalize complex domain knowledge into structured formats for systems like knowledge bases or AI applications. One common challenge is bridging the communication gap, as SMEs may use specialized jargon or have implicit knowledge that's difficult to articulate. Ensuring accuracy while translating this expertise into machine-readable forms requires patience, active listening, and iterative feedback. Building strong relationships and developing effective questioning techniques are essential for overcoming these challenges and delivering high-quality knowledge models.

What engineers make $500,000?

Senior engineers in fields such as software engineering, data engineering, and specialized roles like machine learning engineers can earn $500,000 or more annually, especially with experience, advanced skills, and stock options. High compensation is often associated with leadership positions, working at large tech companies, or in high-demand industries requiring expertise in cloud computing, AI, or cybersecurity.

What are Knowledge Engineers?

Knowledge Engineers are professionals who design, develop, and maintain systems that simulate human knowledge and reasoning. They work at the intersection of computer science, artificial intelligence, and domain expertise to gather and structure information so that machines can use it to solve complex problems. Their responsibilities often include creating knowledge bases, developing ontologies, and implementing rules or logic to enable decision-making in expert systems or AI applications. Knowledge Engineers play a crucial role in enabling organizations to leverage AI for problem solving and automation.

What does a knowledge engineer do?

A knowledge engineer designs, develops, and maintains systems that capture and organize knowledge for artificial intelligence and expert systems. They analyze information, create knowledge bases, and use tools like ontologies and rule-based systems to enable machines to simulate human decision-making. Strong skills in logic, data modeling, and programming are essential for this role.

What is the difference between Knowledge Engineer vs Data Scientist?

AspectKnowledge EngineerData Scientist
Required CredentialsBachelor's or Master's in Computer Science, AI, or related fields; knowledge of ontologies and knowledge basesBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentTypically in AI development teams, focusing on knowledge systems and expert systemsOften in analytics teams, working with large datasets and predictive modeling
Employer & Industry UsageUsed in AI, robotics, and enterprise knowledge managementCommon in tech, finance, healthcare, and marketing sectors

While both roles involve working with data and information, Knowledge Engineers focus on structuring and encoding knowledge for AI systems, whereas Data Scientists analyze data to extract insights and build predictive models. Their skills and tools differ, but both are essential in data-driven industries.

What engineers make $200,000 a year?

Senior software engineers, data engineers, and certain specialized roles such as machine learning engineers often earn $200,000 or more annually, especially with experience, advanced skills, and in high-demand industries. Compensation can also include bonuses, stock options, and other benefits, depending on the company and location.

What are the key skills and qualifications needed to thrive as a Knowledge Engineer, and why are they important?

To thrive as a Knowledge Engineer, you need a solid background in computer science, logic, and knowledge representation, often supported by a relevant degree. Familiarity with semantic web technologies, ontology development tools (like Protégé), and knowledge management systems is typically required. Analytical thinking, attention to detail, and strong communication skills help you effectively translate complex information into structured, usable formats. These capabilities ensure that knowledge systems are accurate, interoperable, and valuable for organizational decision-making.

What Is a Knowledge Engineer?

A knowledge engineer works with data and computer systems with the goal of making the technology imitate human thought processes to solve problems that typically require expertise. Working in a sector of artificial intelligence within the information technology field, a knowledge engineer looks at everyday processes and determines what course of thought a human takes to make a decision or begin an activity. They then create computer systems reliant on this extensive data to guide a machine to simulate human cognition and problem-solving. The data validation process is a vital aspect of a knowledge engineer’s job. They must gather an accurate understanding of the tasks at hand and ensure that the data meets specific standards.

What job categories do people searching Knowledge Engineer jobs in Virginia look for? The top searched job categories for Knowledge Engineer jobs in Virginia are:
Infographic showing various Knowledge Engineer job openings in Virginia as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $98,177 per year, or $47.2 per hour.
Knowledge Management Engineer with Security Clearance

Knowledge Management Engineer with Security Clearance

ECS

Falls Church, VA • On-site

Other

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Job Description Everforth ECS is seeking a Knowledge Management Engineer to work in the National Capital Region covering the Pentagon, Falls Church, and Fairfax. Please Note: This position is contingent upon contract award. The War Data Platform (WDP) is a key initiative within the U.S. Department of War's (DoW) AI-First strategy introduced in early 2026. The WDP focuses on operational warfighting data and aims to accelerate the deployment of artificial intelligence (AI) on the battlefield. The WDP extends to Unclassified, Secret, and Top Secret environments, and supports collaboration between Combatant Commands, Joint Staff directorates, Senior Executive Service leaders, and operational analysts. The Knowledge Management Engineer builds and governs enterprise knowledge management capabilities that equip WDP mission stakeholders with fast, accurate, and intuitive access to the information needed to operate effectively across classified and unclassified environments. This role directly supports WDP's customer experience objectives by delivering AI-assisted content tools, structured self-service resources, and disciplined content governance that reduce Tier-1 ticket volume and accelerate operational readiness across the DoW enterprise. • Builds and maintains enterprise knowledge management capabilities supporting mission stakeholders across multi-enclave environments used for defense analytics programs such as War Data Platform (WDP) Core Integration, Joint All-Domain Decision Support, and headquarters-level operational planning systems.
• Develops structured knowledge repositories using SharePoint, Confluence, and ServiceNow Knowledge Base modules, applying controlled vocabulary design, content classification, metadata tagging, and lifecycle governance to organize standard operating procedures, instructional guides, frequently asked questions, and troubleshooting materials.
• Implements artificial intelligence-assisted content generation and recommendation tools to surface relevant guidance, accelerate issue resolution, and reduce Tier-1 ticket volume.
• Configures self-service portals, graphical interfaces, and automated search experiences to improve user navigation, reduce cognitive load, and align with customer experience design objectives.
• Coordinates with onboarding teams, access management personnel, platform engineers, cybersecurity specialists, and data operations teams to validate content accuracy, incorporate new workflows, and reflect evolving system behaviors.
• Conducts analytics on knowledge base utilization, search failure rates, article helpfulness scores, and self-service resolution percentages to identify gaps, develop new material, and improve content quality.
• Supports operational continuity by producing release notes, change summaries, quick reference guides, and mission updates following major system upgrades or capability deployments.
• Participates in customer engagement sessions, training events, and user community forums to gather feedback and integrate field insights into knowledge artifacts.
• Delivers increased operational readiness, faster information retrieval, and higher service desk efficiency through disciplined knowledge engineering practices and mission-aligned content development.
• Performs other duties as assigned. Required Skills • Current Secret security clearance with the ability to obtain and maintain a Top Secret (TS) security clearance.
• 3 or more years of experience designing, building, and managing enterprise knowledge management systems in a federal government or classified environment, including hands-on development of structured content repositories, self-service portals, and knowledge governance frameworks using platforms such as SharePoint, Confluence, or ServiceNow Knowledge Base.
• Demonstrated experience applying AI-assisted tools, automated search configurations, or retrieval-augmented generation (RAG) techniques to improve knowledge discoverability, content recommendation, and self-service resolution rates within a mission-facing or enterprise IT support environment.
• Strong problem-solving and decision-making capabilities, with a proven ability to weigh the relative costs and benefits of potential actions and identify the most appropriate solution.
• Highly developed interpersonal and oral/written communication skills, with the ability to effectively and professionally interact with a diverse set of stakeholders (from peers to end-users to executive management). Desired Skills • Active Top Secret (TS) security clearance.
• Familiarity with DoW or federal government knowledge management standards, including experience maintaining centralized knowledge repositories in compliance with content lifecycle governance requirements such as archiving, version control, and access-controlled distribution across multi-enclave environments.
• Experience measuring and reporting on knowledge base performance indicators such as search failure rates, article helpfulness scores, and self-service deflection percentages, with demonstrated ability to translate analytics into targeted content improvements.
• Working knowledge of AI/ML content generation tools, large language model (LLM) integrations, or Retrieval-Augmented Generation (RAG) architectures as applied to enterprise knowledge platforms, including familiarity with prompt engineering, domain-specific knowledge grounding, and dynamic policy update capabilities that reduce the need for static user retraining.
• Experience supporting knowledge management functions within an IT service management or help desk environment, including coordination with Tier-1 and Tier-2 support teams to develop troubleshooting content, reduce repeat ticket volume, and align knowledge artifacts with evolving platform capabilities. ECS Federal LLC is an equal opportunity employer and does not discriminate or allow discrimination on the basis any characteristic protected by law. All qualified applicants will receive consideration for employment without regard to disability, status as a protected veteran or any other status protected by applicable federal, state, or local jurisdiction law. is the federal segment of , a $4B global organization with over 10,000 employees. Our nearly 3,500 professionals deliver advanced technology solutions in data and AI, cybersecurity, and enterprise transformation, serving defense, intelligence, and federal civilian agencies. Our work powers mission-critical outcomes, strengthens technology partnerships, and creates meaningful opportunities for our people. We are defined by a commitment to excellence in delivery, a culture of innovation, and an environment where talent can thrive and grow. We value: * Attracting and developing top talent and high-performing teams * Fostering a culture that is engaging, accountable, and mission-driven