AI Graph Engineer

Job Title: AI Graph Engineer (Senior)

Positions Available: x2

Salary: High rates on offer, contact for details - Initial daily pay rate for contract period before converting to salary

Location: Abingdon, outside London

Hours: Full time Monday to Friday

Hybrid: Hybrid working with 2-3 office days in Abingdon - fully remote may be an option for the right candidate

Contract: FULL TIME initial 6 month contract, treating this as a ‘probation’ type period, and if all goes well in the first 3-6 months then transitioning to permanent staff position or extending contract if preferred

Key Experience

Required:

someone that has experienced defining and building semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data.

About the Role

We are seeking a highly skilled AI Agent Engineer with deep experience in Lang Graph
, agentic AI workflows
, ontology-driven knowledge graphs
, and data systems integration
. This role will focus on designing and building agentic workflows that enable natural-language querying across structured and unstructured data to deliver intelligent insights for analytics and decision-making.

Candidate will architect and implement multi-step AI agents, integrate them with enterprise data platforms, and build semantic layers that support reasoning, retrieval, planning, and autonomous task execution across heterogeneous data sources. Experience in Oil & Gas data domains such as drilling, production, subsurface, HSE, or asset operations is highly preferred.

Key Responsibilities Knowledge Graph & Ontology Engineering

• Define and build semantic models, ontologies, and taxonomies aligned with Oil & Gas industry data.
• Architect and maintain knowledge graphs that integrate with enterprise data sources.
• Implement embeddings-assisted retrieval, RAG pipelines, and cross-domain entity linking.

AI Agent & Workflow Development

• Design, build, and scale Lang Graph-based agentic workflows for natural-language data exploration, insights generation, and analytics automation.
• Implement autonomous workflows including planning, retrieval, reasoning, and tool execution.
• Build modular, stateful agents capable of multi-step reasoning, context retention, and complex decision flows.

Data Systems Integration

• Connect AI agents with relational databases (Postgre
  
  SQL, SQL Server, Oracle),
  graph databases (Neo4j, Neptune), and data lakes (S3, ADLS, Delta Lake).
• Build pipelines to ingest, index, and query both structured and unstructured data.
• Develop semantic query layers for NL-to-SQL, NL-to-Graph
  
  QL, or NL-to-SPARQL translations.

Application & API Development

• Build Python services, APIs, and microservices for agent orchestration and data access.
• Collaborate with data engineering, analytics, and domain experts to deploy scalable solutions.

Oil & Gas Domain Expertise

• Understand industry data models such as drilling logs, production data, wellbore schemas, seismic metadata, engineering documents, and operations workflows.
• Translate industry use cases into agentic AI workflows that deliver actionable insights.

Required Skills & Experience Core Technical Skills

• Lang Graph for agent orchestration (planning, memory, tools, multi-agent workflows).
• Python (advanced proficiency).
• Knowledge Graphs
  : building ontologies, semantic models, RDF/OWL, SPARQL.
• Graph Databases
  :
  Neo4j, Neptune or similar.
• Relational Databases
  :
  Postgre
  
  SQL, SQL Server, MySQL, Oracle; query optimization.
• Data Lakes
  : S3, ADLS, Delta Lake, Parquet/Arrow.
• RAG / Vector Databases
  :
  Postgres, Pinecone, Weaviate, Qdrant, Chroma or equivalent.
• Natural Language Query Systems
  : NL-to-SQL, semantic query engines, embedding models.

AI/ML Skills

• Experience with LLM-based systems, prompt engineering, and structured agent design.
• Knowledge of retrieval strategies, hybrid search, and memory architectures.
• Familiarity with OpenAI, Azure OpenAI, Anthropic, or similar model providers.

Architecture & Engineering Skills

• Microservices architecture, API development, containerization (Docker/Kubernetes).
• CI/CD and production ML/AI deployment best practices.

Industry Skills

• Oil & Gas data models and standards (PPDM, WITSML, PRODML, RESQML preferred).
• Understanding of drilling operations, production…