AI Graph Engineer

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, 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 Required: someone that has experience 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 LangGraph, 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 LangGraph-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 (PostgreSQL, 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-GraphQL, 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
  • LangGraph 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: PostgreSQL, 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, subsurface data, or engineering documents.

Preferred Qualifications

• 6-10+ years of experience in data engineering, AI engineering, or knowledge graph engineering.
• 1+ years hands-on experience with LangChain/LangGraph or agentic AI frameworks.
• Experience designing enterprise-scale semantic or knowledge-centric systems.
• Prior experience implementing NLQ (natural language query) for analytics or BI.
• Experience in Oil & Gas digital transformation projects.

Soft Skills

• Excellent problem-solving and conceptual modeling skills.
• Ability to work cross-functionally with data engineering, cloud teams, and business SMEs.
• Strong communication and technical documentation skills.
• Ability to translate ambiguous business requirements into technical workflows.

With over 90 years' combined experience, NES Fircroft (NES) is proud to be the world's leading engineering staffing provider spanning the Oil & Gas, Power & Renewables, Chemicals, Construction & Infrastructure, Life Sciences, Mining and Manufacturing sectors worldwide. With more than 80 offices in 45 countries, we are able to provide our clients with the engineering and technical expertise they need, wherever and whenever it is needed. We offer contractors far more than a traditional recruitment service, supporting with everything from securing visas and work permits, to providing market-leading benefits packages and accommodation, ensuring they are safely and compliantly able to support our clients.