below marketmost similar roles pay hereabove market
This role pays less than
65%
of similar roles. Most pay
$176,250–$246,150
— the blue band above.
At the midpoint, this role pays about
$194k
versus about
$211k
for comparable roles.
Based on 240 similar postings.
Employer
About Accenture
Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.
Accenture currently has
174 open roles
on FindRole.
Listed pay typically runs
$94,400–$266,300
across 128 roles with salary data.
The Knowledge Engineer Manager - Back-end Engineer will join the team to design, build, and operate data infrastructure and services for an AI-driven knowledge platform. This role involves architecting APIs, building data pipelines, and managing multi-modal database systems to ensure reliability and performance. Key responsibilities include hydrating structured and semi-structured data into Knowledge Graphs, developing transformation workflows using R2RML, and optimizing SPARQL queries. The engineer will also deploy vector database infrastructure and maintain scalable graph query APIs. Required technologies include RDF, OWL, SKOS, SPARQL, and R2RML, alongside databases like GraphDB, Stardog, Neo4j, and Amazon Neptune. Proficiency in Python or Java, SQL, and tools such as Docker, Kubernetes, and Kafka is essential for managing ingestion, storage, and retrieval at enterprise scale.
Knowledge Engineering
LLM
Retrieval-Augmented Generation
Knowledge Graph
Data Modeling
Data Taxonomy
Graph-based ML
Symbolic Modeling
Agentic AI
Agile
AI
Knowledge Graphs
LLM
Distributed Systems
APIs
Data Platforms
AI
ML
Ontology
Entity Resolution
Observability
SLOs
Search
Contextual Grounding
Backend Services
Conversational AI
Retrieval-Augmented Generation (RAG)
Large Language Models (LLMs)
Knowledge Graphs
Vector Databases
Distributed Systems
Model Alignment
Knowledge Distillation
Semantic Search
Core ML
Information Retrieval
Ranking Systems
Embedding Models
LLM Inference Optimization
Knowledge Pipelines
Conversational AI
Retrieval-Augmented Generation (RAG)
Large Language Models (LLMs)
Knowledge Graphs
Vector Databases
Distributed Systems
Core ML
Information Retrieval
Semantic Search
Model Alignment
Knowledge Distillation
Embedding Models
LLM Inference Optimization
Ranking Systems
Conversational AI
Retrieval-Augmented Generation (RAG)
Large Language Models (LLMs)
Knowledge Graphs
Vector Databases
Distributed Systems
Core ML
RLHF
RLAIF
Information Retrieval
Semantic Search
Model Alignment
Knowledge Distillation
Embedding Models
Ranking Systems
LLM Inference Optimization