Senior Knowledge Graph Engineer / AI Architect - (100% Remote)

Avesta Computer Services; United States; Remote; USD 90,000 - 105,000; Full time

Job summary

A leading company in AI is looking for a Senior Knowledge Graph Engineer to design and develop enterprise-scale Knowledge Graphs. This remote position offers the chance to work on cutting-edge AI technologies and collaborate with top experts in the field. Competitive compensation and equity are part of the package.

Benefits

Competitive compensation

Equity

Benefits

Qualifications

• 7+ years of experience in software engineering.
• 3+ years focused on Knowledge Graphs or semantic technologies.
• Experience integrating Large Language Models with knowledge graphs.

Responsibilities

• Architect and design scalable Knowledge Graphs using RDF and Neo4j.
• Lead integration of AI models with Knowledge Graphs for inference.
• Guide engineering teams on best practices for graph-based AI systems.

Skills

Graph-based data models

Semantic technologies

AI architectures

NLP

Python

Education

Advanced degree in Computer Science, AI, or related field

Tools

Neo4j

Amazon Neptune

RDF

SPARQL

Job description

Senior Knowledge Graph Engineer Agentic AI - (100% Remote)

Senior Knowledge Graph Engineer Agentic AI - (100% Remote)

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Senior Recruitment Specialist at Avesta Computer Services | Expertise in IT, Non-IT Talent Acquisition

Job Title - Senior Knowledge Graph Engineer / Agentic AI - (100% Remote)

Duration - Contract-To-Hire

Location - 100% Remote

Customer - Our customer is a stealth mode start-up.

Why Join Us

• We are a startup developing a general purpose diagnostics engine
• Work on cutting-edge problems at the intersection of AI reasoning model, knowledge representation, and software architecture.
• Collaborate with world-class engineers, researchers, and domain experts.
• Competitive compensation, equity, and benefits

Position Overview

We are seeking a highly experienced Senior Engineer or Architect to lead the design, development, and deployment of enterprise-scale Knowledge Graphs and AI reasoning systems. The ideal candidate will have deep expertise in graph-based data models, semantic technologies, and AI architectures — including reasoning engines, agents, and multimodal AI systems.

You will work cross-functionally with data scientists, ML engineers, software developers, and domain experts to create intelligent systems capable of representing, reasoning, and learning from structured and unstructured data.

Key Responsibilities

• Architect and design scalable and maintainable Knowledge Graphs using technologies such as RDF, OWL, SHACL, SPARQL, Neo4j, and GraphQL.
• Lead efforts to integrate AI models with Knowledge Graphs to enable inference, logical reasoning, and multi-hop question answering.
• Define and implement semantic enrichment pipelines using NLP, entity linking, relationship extraction, and ontology alignment.
• Collaborate on the development of intelligent agents and autonomous tools that utilize symbolic and sub-symbolic reasoning.
• Guide and mentor engineering teams on best practices for building and using graph-based AI systems.
• Partner with data engineering and platform teams to manage large-scale graph data infrastructure (e.g., AWS Neptune, Blazegraph, TigerGraph).
• Evaluate and implement reasoning engines, including rule-based systems, theorem provers, or differentiable logic layers.
• Prototype and productionize solutions that combine LLMs with structured knowledge for real-time decision support, semantic search, or recommendation systems.
• Author technical documentation, whitepapers, and reusable architectural blueprints.

Required Qualifications

• 7+ years of experience in software engineering, with at least 3+ years focused on Knowledge Graphs or semantic technologies and using AI models.
• Strong experience with RDF, OWL, SPARQL, and related semantic web standards.
• Proficiency in graph databases such as Neo4j, Amazon Neptune, ArangoDB, or equivalent.
• Deep understanding of AI reasoning systems (symbolic AI, rule-based systems, hybrid AI, neuro-symbolic architectures).
• Experience integrating Large Language Models (LLMs) and knowledge graphs using frameworks like LangChain, CrewAI, or similar.
• Familiarity with knowledge representation, ontologies, and taxonomy design.
• Hands-on experience with Python (preferred), Java, or other modern programming languages.
• Exposure to agent-based systems, planning algorithms, or multi-agent frameworks.
• Strong communication skills and ability to lead cross-disciplinary technical discussions.

Preferred Qualifications

• Advanced degree (MS or PhD) in Computer Science, AI, Knowledge Representation, or related field.
• Experience with reasoning engines such as Drools, Prolog, OpenCyc, RDFox, or LogicBlox.
• Experience building AI tools or agents that interact with APIs or tools autonomously.
• Publications or open-source contributions in semantic technologies, AI reasoning, or graph AI.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Job function

  Information Technology

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