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Knowledge Graph Jobs in Virginia (NOW HIRING)

BTI360 Inc

NLP Engineer with Security Clearance

Herndon, VA · On-site

$117K - $141K/yr

As an NLP Engineer at BTI360, you will: • Lead end-to-end knowledge graph and knowledgebase development efforts from problem definition to production, designing pipelines that extract, normalize ...

Enterprise Knowledge

Full Stack AI Developer

Arlington, VA · On-site

$95K - $115K/yr

Work with internal teams to integrate AI components with semantic layers and knowledge graph implementations * API & Middleware: Develop middleware integration layers for decoupled systems, including ...

Enterprise Knowledge

Full Stack AI Developer

Arlington, VA · On-site

$95K - $115K/yr

Work with internal teams to integrate AI components with semantic layers and knowledge graph implementations * API & Middleware: Develop middleware integration layers for decoupled systems, including ...

Navstar

Graph Database Engineer

Chantilly, VA · On-site

$117K - $140K/yr

Stay up-to-date with industry trends and emerging technologies, applying this knowledge to improve ... Strong proficiency working with graph databases (for example JanusGraph) and graph query languages

Enterprise Knowledge

Semantic Modeler

Arlington, VA · On-site

Willingness and ability to develop new skills, especially ontology and knowledge graph development While prior experience developing ontology models and knowledge graphs is not required, you will be ...

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Knowledge Graph information

What are the key skills and qualifications needed to thrive in the Knowledge Graph position, and why are they important?

To thrive as a Knowledge Graph Engineer, you need strong skills in semantic web technologies, ontology modeling, and data integration, typically supported by a background in computer science or data science. Familiarity with tools like RDF, SPARQL, OWL, and knowledge graph platforms (e.g., Neo4j, GraphDB) is common, and certifications in data engineering or semantic technologies are beneficial. Effective communication, problem-solving abilities, and cross-functional collaboration are valuable soft skills in this field. These competencies are crucial for designing, implementing, and maintaining knowledge graphs that enable advanced data discovery and insights for organizations.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like ML engineer or data scientist, are generally well-paid due to the specialized skills required, such as programming, statistics, and knowledge of algorithms. Salaries tend to be higher than average in tech hubs and often increase with experience, certifications, and proficiency in tools like Python, TensorFlow, or PyTorch.

What is a knowledge graph job description?

A knowledge graph job description typically involves designing, developing, and maintaining knowledge graphs that organize and connect data for improved search, reasoning, and data integration. The role often requires skills in data modeling, graph databases like Neo4j, and understanding of semantic technologies such as RDF and OWL. Professionals in this field may work with data scientists, software engineers, and domain experts to ensure accurate and efficient knowledge representation.

What is a Knowledge Graph job?

A Knowledge Graph job typically involves designing, building, and maintaining structured representations of data that map relationships between entities. Professionals in this role work with technologies like RDF, SPARQL, ontologies, and graph databases to enhance data integration, retrieval, and reasoning. These jobs are common in AI, search, and data science fields, helping organizations improve knowledge discovery and decision-making.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI product executive, often requiring advanced skills in data science, programming, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact. Such salaries are rare and generally found in top tech companies or specialized AI firms.

What engineer makes $500,000 a year?

Senior data engineers or machine learning engineers working in high-demand industries such as technology, finance, or AI can earn salaries around $500,000 annually, especially with extensive experience, advanced skills in big data tools, and relevant certifications. Compensation varies based on location, company size, and individual expertise.

What are some typical daily responsibilities of a Knowledge Graph Engineer?

As a Knowledge Graph Engineer, your typical day involves designing and developing ontologies, integrating diverse data sources, and implementing graph-based data models to enhance information accessibility. You may work closely with data scientists, software developers, and business analysts to gather requirements and translate them into scalable knowledge graph solutions. Regular tasks include writing SPARQL queries, performing data mapping, maintaining documentation, and troubleshooting graph data issues. Collaboration and ongoing learning are integral as this field rapidly evolves with new tools and best practices.

What are the most commonly searched types of Knowledge Graph jobs in Virginia? The most popular types of Knowledge Graph jobs in Virginia are:
What are popular job titles related to Knowledge Graph jobs in Virginia? For Knowledge Graph jobs in Virginia, the most frequently searched job titles are:
What job categories do people searching Knowledge Graph jobs in Virginia look for? The top searched job categories for Knowledge Graph jobs in Virginia are:
Knowledge Graph jobs near you
Knowledge Graph Software Engineer - Clearance Required

Knowledge Graph Software Engineer - Clearance Required

BTI360

Herndon, VA • On-site

Full-time

Posted 6 days ago

Job description

Job Summary:
BTI360 is a company passionate about developing software engineers and has been recognized as a top workplace. They are seeking a Knowledge Graph Software Engineer to transform raw data into meaningful insights, focusing on developing scalable graph databases and knowledge bases using emerging AI technologies.
Responsibilities:
• Lead end-to-end knowledge graph and knowledge base development efforts from problem definition to production, designing pipelines that extract, normalize, link, and organize information into scalable graph-based systems.
• Design and evaluate extraction and resolution workflows using sound methodologies and fit-for-purpose metrics to assess entity extraction, linking, relationship quality, and overall knowledgebase completeness and accuracy.
• Translate business requirements into quantitative problems and communicate technical findings to both technical and non-technical stakeholders through reports, presentations, and direct customer engagement.
• Drive technical decision-making for schema design, ontology alignment, extraction approaches, and graph architecture based on mission needs, data quality, and long-term maintainability.
• Stay current with advances in knowledge representation and information extraction and introduce practical techniques, tools, and frameworks that improve graph construction, curation, and analytic value.
• Apply analytical and statistical methods to validate extracted insights, measure data quality, and support confident decision-making from structured and unstructured sources.
• Develop reports and whitepapers that evaluate solution alternatives based on impact, cost, technical feasibility, and alignment with strategic goals.
• Collaborate across teams to align on strategy, provide data science expertise, and contribute to proposals and strategic initiatives.
• Mentor junior data scientists by providing technical guidance, defining project direction, and sharing best practices in graph-oriented data modeling, extraction workflows, and knowledgebase stewardship.
Qualifications:
Required:
• Active Security Clearance (Secret or higher) or the ability to obtain one
• Hands-on experience with graph databases such as Amazon Neptune, Neo4j, or related graph technologies.
• Experience designing and implementing scalable, maintainable, and OOP based software in a containerized cloud environment (AWS preferred) leveraging foundational services for computing, identity management, and networking.
• Experience developing backend services using Java and the Spring/Spring Boot framework (or similar relevant Java framework)
• Effective written and verbal communication skills necessary to perform job duties and collaborate with team members
• Candidates must maintain a primary residence within a two hour drive of Herndon, VA to support onsite collaboration as needed.
Preferred:
• Experience with source control (e.g. Git) and CI/CD pipeline tools such as AWS CodeBuild (preferred), Jenkins, GitLab CI, or GitHub Actions
• Experience with testing frameworks such as Junit (preferred), Mockito, or Spring Runner
• Familiarity with monitoring and observability stacks such as Prometheus/Grafana (preferred), CloudWatch, or ELK/EFK
• Experience with search technologies such as OpenSearch (preferred), Elasticsearch, or Solr
• Experience working with streaming or event-driven architectures such as SNS/SQS (preferred), Kafka, Kinesis, AWS Step Functions, or Event Bridge
• Familiarity with monitoring and observability stacks including OpenTelemetry, Splunk (preferred), Prometheus/Grafana, or CloudWatch
Company:
BTI360 develops and delivers big data software solutions to minimize the time spent on research and utilize time providing insights. Founded in 2004, the company is headquartered in Ashburn, USA, with a team of 51-200 employees. The company is currently Growth Stage.

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