Lead AI/ML Engineer – Knowledge Graphs & GenAI

TechDigital Group; Dallas (TX); On-site; USD 140,000 - 240,000; Full time

Job summary

TechDigital Group seeks an experienced AI/ML Engineer specializing in knowledge graphs and generative AI to design, build, and scale enterprise-grade data pipelines converting unstructured data into Knowledge Graphs.

You will work on ontology modeling, entity resolution, and graph-based reasoning, integrating LLMs with knowledge graphs for contextual intelligence and anomaly detection at scale.

Qualifications

• Extensive hands-on AI/ML engineering with knowledge graphs and generative AI.
• Experience designing ontology models and entity resolution across large data sources.
• Proficiency in building scalable data pipelines and production-grade AI systems.

Responsibilities

• Design, build, and maintain enterprise-scale Knowledge Graphs from large volumes of unstructured data.
• Create and evolve ontologies using RDF/OWL, including entity extraction, resolution, and alignment.
• Develop agentic AI systems for knowledge-base enrichment and continuous learning of graph pipelines.
• Design and implement AI/ML pipelines integrating LLMs, SMLs, and reasoning models.
• Apply prompt engineering, RAG, and graph-based reasoning for contextual intelligence.
• Develop anomaly detection and analytics atop knowledge graph data.

Skills

Python

LLMs/SMLs

GenAI

Knowledge graphs

Ontology engineering

Entity resolution

Graph databases

MLOps

Cloud platforms

Data pipelines

Tools

Neo4j

GraphDB

Cypher

SPARQL

LangChain

LangGraph

LlamaIndex

Pinecone

FAISS

Azure ML

MLflow

Datadog

Job description

TechDigital Group seeks an experienced AI/ML Engineer specializing in knowledge graphs and generative AI to design, build, and scale enterprise-grade data pipelines converting unstructured data into Knowledge Graphs.

You will work on ontology modeling, entity resolution, and graph-based reasoning, integrating LLMs with knowledge graphs for contextual intelligence and anomaly detection at scale.