AI Graph Engineer

Position: AI Graph Engineer (Permanent)
Location: Sutton Wick

Job Title:

AI Graph Enineer (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
Hyrbid:
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, they are treating this as a ‘probation’ type period, and if all goes well in the first 3-6 months then they will transition you into a permanent staff position or extend the contract if preferred

Key Experience Requried: someone that has experience defining and buildig 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  & 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 operations,…