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Llm Knowledge Graph Jobs in Reston, VA (NOW HIRING)

... LLM-based workflows, or knowledge graph applications. • You have experience in evaluation design, operational test and evaluation, or scenario-based product assessment. • You have created ...

... LLM-based workflows, or knowledge graph applications. • You have experience in evaluation design, operational test and evaluation, or scenario-based product assessment. • You have created ...

AI Developer

Mclean, VA

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

AI Developer

Mclean, VA

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

AI Developer

Mclean, VA · On-site

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

AI Developer

Mclean, VA · On-site

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

AI Developer

Mclean, VA

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

AI Developer

Mclean, VA · On-site

$140K - $190K/yr

Develop end-to-end AI solutions including LLM-powered applications, predictive ML models, multi ... Working knowledge of vector and relational data stores including AWS RDS Postgres (pgvector) and ...

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Llm Knowledge Graph information

See Reston, VA salary details

$42.7K

$65.9K

$99.4K

How much do llm knowledge graph jobs pay per year?

As of Jun 27, 2026, the average yearly pay for llm knowledge graph in Reston, VA is $65,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,100.00 and $72,300.00 per year, depending on experience, location, and employer.

What is the difference between Llm Knowledge Graph vs Data Scientist?

AspectLlm Knowledge GraphData Scientist
Required CredentialsKnowledge of NLP, graph databases, machine learningStatistics, programming, data analysis
Work EnvironmentResearch labs, AI companies, tech firmsCorporate, consulting, research institutions
Industry UsageAI, knowledge management, semantic webBusiness analytics, predictive modeling

While both roles involve data and machine learning, Llm Knowledge Graph specialists focus on building interconnected knowledge bases using NLP and graph technologies, whereas Data Scientists analyze data to extract insights and build predictive models. The roles often overlap in AI projects but serve different core functions within organizations.

What are popular job titles related to Llm Knowledge Graph jobs in Reston, VA? For Llm Knowledge Graph jobs in Reston, VA, the most frequently searched job titles are:
What cities near Reston, VA are hiring for Llm Knowledge Graph jobs? Cities near Reston, VA with the most Llm Knowledge Graph job openings:

AI Security Automation Engineering - Lead

Kanor Systems

Bethesda, MD • On-site

Other

Posted 13 hours ago


Job description

Role Level

Lead/Manager- AI Security Automation Engineering

Role Type

Individual Contributor

Location

Remote-friendly / Marriott HQ

Core Stack

Python Go Neo4j LLM APIs Graph Databases

Frameworks

NIST AI RMF OWASP LLM Top 10 ISO 42001 OSCAL

Responsibilities:

  • Design review templates ("archetypes") for every major AI deployment pattern: agentic AI, conversational platforms, IoT+AI, contact center AI, and enterprise SaaS.
  • Build intake questionnaires that auto-route submissions to the right control checklists based on deployment model (SaaS, on-prem, hybrid, multi-cloud, API-integrated).
  • Define complexity weighting models and set measurable cycle-time targets per review type.
  • Build LLM-powered tools that auto-draft threat models from architecture descriptions, map controls to findings, and surface cross-review risk patterns.
  • Develop automated intake and triage pipelines - intent classification, complexity scoring, archetype detection, priority assignment - integrated with ServiceNow or Jira.
  • Own the operational dashboards: cycle time, queue depth, completion rate, rework rate.
  • Design and maintain a labeled property graph ontology connecting AI patterns, controls, threats, standards, deployment paradigms, and risk tiers.
  • Implement graph traversal queries for gap analysis (risk dimension unaddressed controls), tier compliance, and cross-pattern coverage.
  • Export graph data to support executive reporting and audit evidence packages.
  • Build control mapping pipelines that link review findings to AI risk dimensions and OSCAL-aligned compliance attestations.
  • Drive alignment with EU AI Act obligations: risk classification, quality management traceability, and risk management documentation.
  • Coordinate with assurance and risk teams on scoring handoff criteria and independent verification.

Must-Have Experience

  • 10+ years building and operating complex data models, knowledge graphs, or system architectures - especially in compliance, policy, or regulatory domains.
  • 2+ years in cybersecurity: security assessments, threat modeling, control mapping, or risk analysis in enterprise or regulated environments.
  • Proven track record converting manual review processes into repeatable, metrics-driven, AI-assisted operations.
  • Experience building AI/ML automation for security, compliance, or GRC workflows - not just using tools, but engineering them.
  • Production-grade delivery: automation systems running at enterprise scale, not proof-of-concept only.
  • Strong executive communication: able to present pipeline metrics upward and threat models to architecture review boards.

Technical Skills

  • Python and Go for building automation tooling, API integrations, and data pipelines.
  • Graph databases: Neo4j, KuzuDB, NetworkX, openCypher, or GraphML - including ontology design and graph-based reasoning.
  • LLM and agent frameworks: PydanticAI, LangChain, or equivalent; experience with Claude (Bedrock), Azure OpenAI, or similar foundation model APIs.
  • AI system architecture depth: LLMs, RAG pipelines, MCP, vector stores, agent orchestration.
  • Security frameworks: NIST AI RMF, ISO 42001, NIST CSF, OWASP LLM Top 10, OWASP Agentic Top 10, MITRE ATLAS, OSCAL.
  • Workflow platform APIs: ServiceNow, Jira, or equivalent for end-to-end process automation.

Education

  • Master's or Ph.D. in Computer Science, Cybersecurity, Information Systems, or related STEM field - or equivalent experience demonstrated in role.