Knowledge Engineering Senior Analyst

Accenture PLC; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Accenture plc in London is seeking a strong individual contributor knowledge engineer evolving into a team lead to transform real-world problems into scalable AI and knowledge graph solutions, working hands‑on from ingestion to deployment. You will guide junior engineers and collaborate with users, architects and product teams.

You will apply current knowledge engineering, LLM and multi‑modal techniques, design ontologies, and help articulate the business value of AI and KG approaches to clients

Qualifications

• Bachelor's degree or equivalent plus at least three of the listed requirements.
• Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL).
• Experience in schema design, ontology management, and KG curation.
• Experience designing and developing KG solutions and graph-based ML models.
• Experience with end-to-end data pipelines for AI apps (LLMs).
• Strong knowledge of relational and graph databases and vector stores.

Responsibilities

• Build Knowledge Graph components transforming client data architectures.
• Design, develop, and implement AI and semantic solutions integrated with the broader system.
• Collaborate with project team and delivery leads.
• Develop solid client relationships on the workstream.
• Contribute evidence for the recommended semantic layer solution.
• Support Accenture sales efforts when called on.
• Keep skills in cutting-edge Data & AI solutions and share with the team.

Skills

Knowledge Graph technologies

Schema design

KG curation

KG solutions and graph-based ML models

End-to-end data pipelines for AI

Relational & graph databases

NLP and/or Search techniques

Prompt engineering and LLMs

External client-facing consulting

Agentic systems

Education

Bachelor's degree or equivalent

Tools

Python

TensorFlow

PyTorch

Apache NiFi

Airflow

Job description

YOU ARE

You are a a strong individual contributor knowledge engineer growing into a team lead. You are well versed in the full knowledge graph development lifecycle. You formulate real-world problems into practical, efficient, scalable AI and Knowledge Graph solutions, working hands‑on across the lifecycle from ingestion through modeling, curation, and deployment. You apply current methodologies, techniques, and algorithms with the right architecture, and begin to guide junior engineers on the project. You stay current with knowledge engineering, generative AI, LLM, and multi-modal models; look for opportunities to apply them to the problem at hand. You design, evaluate, and maintain ontologies as needed. You help articulate the value of generative AI and knowledge graph approaches for a given business problem. You share what they learn with the team. You collaborate with users, use case reps, engineers, architects, and UI designers to deliver their piece of an end‑to‑end solution.

THE WORK

• Build Knowledge Graph components that contribute to transforming a client's data architecture.
• Design, develop, and implement AI and semantic solutions; ensure their work integrates cleanly with the broader system.
• Work alongside the project team and delivery leads.
• Build solid working relationships with client counterparts on their workstream.
• Help assemble the supporting evidence for the recommended semantic layer solution.
• Support Accenture sales efforts when called on.
• Keep developing skills in cutting‑edge Data & AI solutions, especially agentic technologies, and shares with the team.

BASIC (REQUIRED) QUALIFICATION

• Bachelor's degree or equivalent, plus at least 3 of the following:
• Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)
• Experience in schema design, ontology management, and KG curation
• Expertise in designing and developing KG solutions and graph-based ML models (functional + technical)
• Experience with end-to-end data pipeline implementation for AI applications (esp. LLMs), with hands‑on design and configuration
• Experience with strong knowledge of relational databases, object stores, graph databases (Stardog, Neo4J, Amazon Neptune), and vector databases

PREFERRED QUALIFICATION

• Hands‑on experience with cloud platforms (AWS, Azure, GCP)
• Experience in Python, with experience in frameworks like Tensorflow, PyTorch, and tools for building ETL pipelines (e.g. Apache NiFi, Airflow)
• Practical experience with NLP and/or Search techniques
• Prompt engineering, and LLMs for enterprise‑scale applications.
• You have team lead experience
• Strong collaboration skills with the ability to work across engineering, research, and product teams across multiple time zones.
• You have external client‑facing consulting experience
• Broad experience in diverse ML techniques and agentic systems