Principal / Lead AI ML Engineer - Knowledge Graphs & GenAI

Principal / Lead AI ML Engineer – Knowledge Graphs & GenAI

Our client, a IT Services and Consulting company, is looking for a Principal / Lead AI ML Engineer – Knowledge Graphs & GenAI for their Dallas, TX location.

Responsibilities:

• Knowledge Graph & Ontology Engineering
• Design, build, and maintain enterprise scale Knowledge Graphs from large volumes of unstructured data (text, documents, logs, PDFs, web data).
• Create and evolve ontologies using RDF/OWL, including:
• Entity extraction and linking
• Entity resolution and disambiguation
• Probabilistic pattern matching
• Ontology alignment across heterogeneous data sources
• Implement semantic modeling for complex domains to support reasoning, discovery, and analytics.
• Agentic Knowledge Base Enrichment

Develop agentic AI systems for:

• Automated data gap identification
• Knowledge base enrichment and validation
• Continuous learning and self improving graph pipelines
• Build workflows that combine LLM reasoning with graph traversal and inference.
• AI/ML & GenAI Systems

Design and implement AI/ML pipelines integrating:

• Large Language Models (LLMs)
• Small Language Models (SMLs)
• Reasoning and task specific models
• Build fine tuning pipelines, including:
• Dataset generation and curation
• Training and fine tuning (SFT, PEFT, adapters)
• Evaluation, benchmarking, and deployment
• Apply prompt engineering, RAG, and hybrid LLM + Knowledge Graph (GraphRAG) techniques for contextual intelligence.

Anomaly Detection & Analytics:

• Develop anomaly detection systems on top of knowledge graph data at scale.
• Apply graph analytics, embeddings, and ML techniques to detect:
• Semantic inconsistencies
• Behavioral anomalies
• Data quality and relationship drift

Data & ML Engineering:

• Build robust data pipelines that ingest, process, enrich, and publish knowledge graph data.
• Implement scalable ML systems using Python for:
• Model development
• Training and tuning
• Inference and deployment

Requirements:

• Core AI/ML
• Strong AI/ML engineering background with deep expertise in:
• Python
• Model development, training, tuning, and deployment
• Extensive hands on experience with:
• Large Language Models (LLMs)
• Small Language Models (SMLs)
• Generative AI and reasoning models
• Text generation, summarization, and semantic search workflows
• Knowledge Graph Technologies
• 10+ years of hands on experience in AI/ML engineering, with strong depth in knowledge graphs, unstructured data processing, and generative AI systems.
• Neo4j, GraphDB
• RDF, OWL
• Cypher, SPARQL

Proven ability to implement:

• Entity linking and resolution
• Semantic search
• Relationship mapping and inference

GenAI Frameworks & Tooling:

• Experience building GenAI systems using:
• LangChain, LangGraph
• LlamaIndex
• OpenAI / Azure OpenAI
• Vector databases such as Pinecone and FAISS

MLOps & LLMOps:

• Strong experience in MLOps and LLMOps, including:
• MLflow, Azure ML, Datadog
• CI/CD automation for ML systems
• Observability, logging, and tracing
• Model performance monitoring and drift detection
• Experience deploying and operating AI systems in production environments.

Cloud & Scalability

• Experience building and optimizing AI/ML and graph pipelines either of any on:
• Azure
• AWS
• GCP
• Strong understanding of distributed systems, scalability, and performance optimization.

Client is looking for candidates who have experience in building:

• Ontology from large scale data (requires experience in entity resolution, probabilistic pattern matching)
• Agentic knowledge-base enrichment (automated data gap identification, and data enrichment)
• Anomaly detection on top of knowledge graph data at scale
• Fine tuning pipeline (including dataset generation, tuning, evaluation, deployment) for small language models and reasoning models
• Years of Experience: 14.00 Years of Experience

Skills:

• Generative AI - OPS Closed Source LLM Yes 1

Why Should You Apply?

• Health Benefits
• Referral Program
• Excellent growth and advancement opportunities