Backend Engineer: Knowledge Graph & AI

Accenture; Pittsburgh (Allegheny County); Hybrid; USD 63,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Travel to client locations

Job summary

Accenture is seeking a Back-End Engineer to design, build, and operate data infrastructure that powers an AI-driven Knowledge Platform. You will map data to ontology models, create data pipelines, build graph services, and own vector store infrastructure to enable semantic retrieval at enterprise scale.

You will work across back-end stacks, optimize relational schemas, and ensure data quality, security, and performance. Hybrid work model and significant travel to client sites are expected.

Qualifications

• Minimum 3 years experience in Knowledge Graph data hydration and ontology-based data mapping, including strong understanding of RDF, SPARQL, and semantic technologies.
• Minimum 3 years experience with R2RML or similar mapping frameworks for transforming relational data into graph models.
• Minimum 3 years experience with graph databases (e.g., StarDog, GraphWise, Neo4J), along with Elasticsearch/OpenSearch, including strong SQL proficiency.
• Minimum 3 years hands-on experience with relational databases (e.g., PostgreSQL, MySQL, or SQL Server), including schema design, indexing, and query optimization.
• Minimum 3 years experience deploying and operating vector databases (e.g., Pinecone, Weaviate, Milvus, or Qdrant) in production environments.
• Minimum 3 years Proficiency in Python or Java for automation, integration, and service development and experience designing and documenting REST APIs for internal consumers.
• Bachelor's degree or equivalent (minimum 12 years) work experience.

Responsibilities

• Hydrate structured and semi-structured data into Knowledge Graphs by mapping source data to ontology models.
• Develop data mapping and transformation workflows using R2RML or similar technologies.
• Write and optimize SPARQL queries for graph loading, validation, and retrieval.
• Build and maintain data ingestion pipelines and integrate data from enterprise systems.
• Design and optimize relational database schemas and queries to support efficient graph hydration and ETL workflows.
• Deploy, configure, and maintain vector database infrastructure for embedding storage, indexing, and semantic retrieval at scale.
• Design and maintain scalable graph query APIs consumed by internal application and product teams.
• Performance-tune graph database queries, indexing strategies, and data access patterns.
• Own containerization, deployment, and monitoring of graph services in cloud environments.
• Ensure data quality, ontology alignment, and secure handling of sensitive data (PII/PHI).
• Collaborate with ontologists, architects, and application teams to support Knowledge Graph implementations.

Skills

Knowledge Graphs

RDF/SPARQL

R2RML

Graph Databases

SQL

Python/Java

REST APIs

Data Pipelines

Cloud Platforms

Education

Bachelor's degree or equivalent (minimum 12 years) work experience

Tools

Docker

Kubernetes

Elasticsearch/OpenSearch

PostgreSQL

Neo4j

Job description

Accenture is seeking a Back-End Engineer to design, build, and operate data infrastructure that powers an AI-driven Knowledge Platform. You will map data to ontology models, create data pipelines, build graph services, and own vector store infrastructure to enable semantic retrieval at enterprise scale.

You will work across back-end stacks, optimize relational schemas, and ensure data quality, security, and performance. Hybrid work model and significant travel to client sites are expected.