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Knowledge Engineer Jobs in Maryland (NOW HIRING)

Ultimate Knowledge

AI Workflow Engineer

Columbia, MD · Remote

About UKi Since 1999, Ultimate Knowledge Institute has set the standard for cybersecurity training ... Level up developer experience. Bring modern AI integrations into the daily workflow of our ...

Unisity LLC

Agile Developer L3 - Knowledge

Annapolis, MD · On-site

$200K - $210K/yr

The Microservices Developer will be responsible for: * Writing java spring boot based micro service ... Government contract rates; education; relevant prior work experience, knowledge, skills, and ...

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How much do knowledge engineer jobs pay per hour?

As of Sep 8, 2026, the average hourly pay for knowledge engineer in Maryland is $46.21, according to ZipRecruiter salary data. Most workers in this role earn between $38.03 and $56.01 per hour, depending on experience, location, and employer.

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 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 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 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.

How much do knowledge engineers make?

Knowledge engineers typically earn a median annual salary between $80,000 and $120,000, depending on experience, education, and industry. Senior roles or those with specialized skills in artificial intelligence and data management can earn higher salaries, often exceeding $150,000. Compensation may also include benefits such as bonuses and stock options.
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Knowledge Engineer jobs near you
Infographic showing various Knowledge Engineer job openings in Maryland as of September 2026, with employment types broken down into 1% As Needed, 80% Full Time, 17% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $96,109 per year, or $46.2 per hour.

Data Engineer (Knowledge Graph Specialist)

Bethesda, MD • On-site

Black Cape
Software Development • 11 - 50 employees
Learn more about Black Capeexternal

$119K - $143K/yr

Full-time

Retirement

Re-posted 11 hours ago

Job description

Black Cape
Title: Data Engineer (Knowledge Graph Specialist)
Location: Bethesda, MD
Onsite: Expected to go onsite (into a SCIF) 3 - 5 days per week
Clearance: TS/SCI - willing to get a CI poly
***MUST have an Active TS/SCI clearance and willing to get a CI Poly***
***If you do NOT have a US Citizenship or a Security Clearance issued by a US Government Customer, we will likely not get back to you. It is a REQUIREMENT of the job.***
Black Cape has Won "Best Places to Work" every year in existence by either the Washington Business Journal & Virginia's Best Places to Work!
Want to be a part of an intelligent, talented, dynamic, and FUN team and keep building something GREAT?? Then, you should consider Black Cape!
  • We work with Department of War (DoW) and Intelligence Community (IC) customers to accomplish their missions
  • Come join us to work on cloud-native full-stack web applications, advanced data analysis tools, and machine learning capabilities
  • Be a part of a team that is making an impact and HAVE FUN while doing so!
About the company:
Black Cape is a unique technology company with a focus on full-stack web applications, advanced data analysis tools, and integrating AI/ML capabilities for federal government customers. We are a COOL and FUN crew that works hard and plays maybe even a little harder. Our core team is an impressive group of engineers with exceptional leadership at the helm.
Black Cape is led by proven business and engineering leaders with a track record of building innovative technology companies focused on building mission applications. We support many programs and agencies as both a prime and a subcontractor and created a strong reputation working with top tier partners doing work for all major Intelligence Community agencies, DoW, and Special Operations customers.
Our engineer-led software teams develop technical solutions on an aggressive schedule across the DoW and IC to meet customer needs. Our engineers apply proven, repeatable software, technical, and analytical approaches to build solutions and have frequent interaction with end users to produce and deploy solutions.
We bring experience in building, integrating and deploying AI/ML solutions using Google TensorFlow, Python scikit-learn, and other tools. Black Cape's approach to solution development combines lessons learned from developing and deploying applications to customer cloud environments with industry best practices in Agile development and DevOps.
What we are hiring:
Intelligence analysts with technical know-how to represent the next generation of object-based intelligence globally. People who want to change the current landscape of tools available to other analysts globally and help make sense of an ever-changing world.
An ideal candidate has a background in the intelligence community, specifically in defense intelligence, and knows how to tackle problems around operational readiness and disposition. Ability to work with technical teams is a must. Must have the ability to effectively communicate ideas about how to utilize the system we're building to other analysts, senior stakeholders, and other parties. Preferred candidates also have the ability to help build training materials in conjunction with the technical team.
Required Technical Skills (MUST HAVES):
  • Must have a Bachelor's degree and 1.5+ years of professional experience
  • A strong grasp of graph theory, data modeling, and a passion for structuring complex, multi-dimensional relationships
  • Expertise with graph database solutions, such as Anzograph, Neo4j, or Amazon Neptune
  • Familiarity with database query languages including Cypher, SQL, and SPARQL
  • Familiarity with scripting languages including Python and shell scripting
  • Familiarity with Linux systems including RedHat-based distributions
  • Experience working with software development teams in any capacity
  • Experience working in and willingness to work in classified government environments
  • Experience developing on MacOS, Windows, and Linux

Preferred Technical Skills (NICE TO HAVES):
  • Experience with AWS Console including but not limited to lite management of EC2 instances
  • Background working with Object-Based Intelligence
  • Background communicating to senior stakeholders in a classified environment
  • CompTIA Security+ certification

Great Benefits | 401K | Competitive Salary | Generous Time Off | Exceptional Team-Building & Fun Company Events | Mentorship & Professional Development Programs | Tuition Reimbursement | Parental Leave Policy

Apply