AI/ML Engineer (Knowledge Graph + GenAI)

Role: AI/ML Engineer (Knowledge Graph + GenAI)

Location: Dallas, TX or Charlotte, NC (Onsite – Local candidates only)

Contract: Long Term Contract

Job Description:

We are seeking an experienced AI/ML Engineer with 8+ years of experience in Generative AI, Knowledge Graphs, and Agentic AI to design and build scalable AI-driven data solutions. The role focuses on transforming large-scale unstructured data into enterprise-grade Knowledge Graphs and enabling intelligent automation, quality analysis, and decision support systems.

The candidate will develop AI-powered pipelines for data ingestion, entity extraction, and relationship mapping using advanced NLP and LLM-based techniques. They will build and enhance AI-driven Quality Analysis and Quality Control (QA/QC) workflows to evaluate and improve Issue Intake processes using prompt engineering, orchestration, and standardized frameworks.

The role also involves designing and implementing Knowledge Graph models to represent risks, issues, controls, and policies, enabling contextual reasoning and real-time recommendations. The engineer will integrate GenAI with Knowledge Graphs to support entity linking, semantic enrichment, and intelligent insights.

Additionally, the candidate will work on AI orchestration, prompt management (templates, chaining, versioning), and workflow automation while ensuring strong observability, governance, and auditability of AI systems. This includes implementing logging, monitoring, performance tracking, and maintaining compliance with enterprise standards.

The ideal candidate should have strong experience in Python, Machine Learning, NLP, LLMs, Knowledge Graph technologies (Neo4j, RDF/SPARQL), cloud platforms (AWS/Azure/GCP), and data pipeline tools. Experience with MLOps, Docker, Kubernetes, and CI/CD is highly preferred.

Strong analytical skills, problem-solving ability, and experience working in enterprise or compliance-driven environments are essential for success in this role.

All your information will be kept confidential according to EEO guidelines.