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Knowledge Engineer Jobs in Maryland (NOW HIRING)

AnaVation

Knowledge Manager

Bethesda, MD · On-site

$95K - $115K/yr

As our Knowledge Manager you would provide access and knowledge management for a variety of managed ... We deliver groundbreaking research with advanced software and systems engineering that provides an ...

HII's Mission Technologies division

$85K - $258K/yr

Our capabilities in cybersecurity, network architecture, reverse engineering, software and hardware ... Knowledge Manager 1 : 90,000-110,000 Knowledge Manager 2 : 130,000-140,000 Knowledge Manager 3 : ...

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$46

$71

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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What are the most commonly searched types of Knowledge Engineer jobs in Maryland?

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For Knowledge Engineer jobs in Maryland, the most frequently searched job titles are:

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The top searched job categories for Knowledge Engineer jobs in Maryland are:

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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.

Kafka Engineer

Woodlawn, MD

Careers | Office of the Inspector General
See more jobs at Careers | Office of the Inspector Generalexternal

$143K/yr

Full-time

Re-posted 6 days ago

Job description

IT Specialist (APPSW) Kafka Engineer positions are being filled through the Office of Personnel Management's delegated Direct Hire Authority, open to all U.S. citizens. Selections made under this bulletin will be processed as new appointments to the civil service. Current civil service employees would, therefore, be given new appointments to the civil service. Under the provisions of the Direct Hire Authority, Veterans Preference and the "Rule of Many" do not apply.Qualifications:Resumes exceeding two pages in length will not be considered, please visit the new resume guidance for more information.
Duties
  • Design, develop, and maintain robust Kafka-based applications and data pipelines that support SSA's business operations, including the real-time or near-real-time data to AI/ML models.
  • Collaborate with development, operations, and infrastructure teams to deliver reliable, scalable, and high-performing Kafka solutions.
  • Ensure the availability, reliability, and performance of Kafka clusters and related systems.
  • Work closely with architects, data engineers, and stakeholders to define requirements and deliver solutions.
  • Troubleshoot and resolve issues in Kafka applications, ensuring minimal downtime and optimal performance.
  • Document code, design decisions, processes, configurations, and best practices for future reference and team knowledge sharing.
  • Mentor junior developers and share Kafka expertise, fostering a culture of learning and growth.
  • Stay current with the latest Kafka releases, features, and ecosystem advancements.
  • Perform statistical analysis to monitor team performance, improve processes, and ensure customer satisfaction.
  • Define and set SLAs for projects, ensuring high standards of service delivery.

READ ALL SECTIONS OF THIS ANNOUNCEMENT IN ITS ENTIRETY. THIS INFORMATION IS CRUCIAL TO SUBMITTING A SUCCESSFUL APPLICATION.
Applicants must qualify for the series and grade of the posted position. Experience must be IT related; the experience may be demonstrated by paid or unpaid experience and/or completion of specific, intensive training (for example, IT certification), as appropriate. Your resume must provide sufficient experience and/or education, knowledge, skills, abilities, and proficiency of any required competencies to perform the specific position for which you are applying.
To qualify for the 2210 IT Specialist series, the applicant must demonstrate the following competencies:
  • Attention to Detail - Is thorough when performing work and conscientious about attending to detail.
  • Customer Service - Works with clients and customers (that is, any individuals who use or receive the services or products that your work unit produces, including the general public, individuals who work in the agency, other agencies, or organizations outside the Government) to assess their needs, provide information or assistance, resolve their problems, or satisfy their expectations; know about available products and services; and is committed to providing quality products and services.
  • Oral Communication - Expresses information (for example, ideas or facts) to individuals or groups effectively, taking into account the audience and nature of the information (for example, technical, sensitive, controversial); makes clear and convincing oral presentations; listens to others, attends to nonverbal cues, and responds appropriately.
  • Problem Solving - Identifies problems; determines accuracy and relevance of information; uses sound judgment to generate and evaluate alternatives, and to make recommendations.

Minimum Qualifications: Grade 14 To qualify at the GS-14 level, you must have specialized experience at the GS-13 level, or equivalent, designing, developing, and maintaining scalable, fault-tolerant data pipelines using Apache Kafka; managing and administering Kafka clusters throughout the Systems Development Life Cycle (SDLC), including upgrades and patching; leading large-scale projects, serving as a Product Owner or Agile/Scrum team lead; demonstrating strong programming skills in Java, with Python experience as a plus; utilizing Kafka APIs (Producer, Consumer, Streams, Connect) for event-driven and microservices-based solutions; applying knowledge of serialization formats (Avro, Protobuf, JSON) and schema registry/data governance, including Hackolade for data modeling; optimizing producer/consumer performance and handling large-scale data ingestion; implementing unit and integration testing for Kafka applications; configuring and tuning Kafka clusters for performance, reliability, and scalability; monitoring and troubleshooting Kafka clusters using tools such as Prometheus and Grafana; supporting hybrid integration architecture patterns.
Minimum Qualifications: Grade 15 To qualify at the GS-15 level, you must have specialized experience at the GS-14 level, or equivalent, leading the design, development, and implementation of enterprise-scale, fault-tolerant data pipelines using Apache Kafka; providing expert-level management and administration of Kafka clusters throughout the Systems Development Life Cycle (SDLC), including upgrades and patching; overseeing large-scale, cross-functional projects as a senior Product Owner or Agile/Scrum leader, ensuring alignment with organizational goals; demonstrating advanced proficiency in Java programming, with experience in Python as a plus; architecting event-driven and microservices-based solutions leveraging Kafka APIs (Producer, Consumer, Streams, Connect); establishing and enforcing best practices for serialization formats (Avro, Protobuf, JSON) and schema registry/data governance, including Hackolade for data modeling; directing the optimization of producer/consumer performance and large-scale data ingestion strategies; leading the implementation of unit and integration testing frameworks for Kafka applications; managing hybrid integration architecture patterns and ensuring reliability, scalability, and performance of Kafka clusters; overseeing monitoring and troubleshooting activities using tools such as Prometheus and Grafana; providing technical guidance and mentorship to teams on Kafka cluster setup, configuration, and tuning; ensuring compliance with organizational standards and data governance policies.
PLEASE NOTE: This specialized experience is REQUIRED and must be explicitly documented/described in your resume, or you will be disqualified from further consideration.
You may be asked to take a Code Signal online assessment.
Qualification standards and additional information for this position can be found here: http://www.opm.gov/policy-data-oversight/classification-qualifications/general-schedule-qualification-standards/2200/information-technology-it-management-series-2210-alternative-a/Education:This job does not have an education qualification requirement.Employment Type: OTHER

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