Senior Knowledge Graph Engineer

EcoVadis; Warszawa; Hybrid; PLN 260,000 - 380,000; Full time

Benefits offered by this job

Hybrid work in Warsaw

Wellness allowance

Professional development

Flexible working hours

Health care options

Employee referral program

Job summary

EcoVadis is seeking a hands-on Senior Knowledge Graph Engineer to operationalize ontology designs into high-throughput graph systems. You will power autonomous AI agents tackling sustainability challenges by linking unstructured disclosures with graph databases and building scalable, multi-hop workflows.

You will work with GraphRAG, NLP pipelines, and SHACL-based data quality tests to ensure reliable, enterprise-grade data. Hybrid in Poland, with remote flexibility.

Qualifications

• 4+ years in production with graph databases
• Strong Python for data pipelines
• Experience with NLP frameworks or LLM-based extraction
• Knowledge of RDF/OWL/SHACL and SPARQL/Cypher
• Cloud experience, preferably Azure

Responsibilities

• Design, implement, and maintain high-speed GraphRAG ingestion pipelines
• Build entity resolution and deduplication workflows
• Federate internal data with external ontologies and registries
• Develop NL2Query tools and MCP endpoints for LLM agents
• Ensure data quality with SHACL in CI/CD
• Optimize multi-hop queries and graph performance

Skills

Graph databases

Python

NLP frameworks

Labeled Property Graphs

Cypher & SPARQL

Education

Degree in Computer Science/Engineering

Tools

Neo4j

Memgraph

TigerGraph

GraphDB/Stardog/Virtuoso

Job description

Work smart, have fun and make an impact! EcoVadis is the leading provider of business sustainability ratings. Our solutions are backed by an international team of experts and powerful technology. We analyze data and build sustainability scorecards that give companies actionable insights into their environmental, social and ethical risks.

Why apply to EcoVadis? Be a part of the global sustainability change in business. Grow your career. Work with extraordinary people. Feel valued for your contribution.

Learn more about our team and culture on EcoVadis careers page.

Job Description

We are looking for a hands‑on, production‑focused Senior Knowledge Graph Engineer to join our growing AI Center of Excellence, responsible for using AI and machine learning to drive innovation across the organization. In this role, you will take the formal domain ontologies designed by our Knowledge Representation Architects and operationalize them into high‑throughput, multi‑hop systems.

Your work will directly power autonomous AI agents that solve complex sustainability challenges — including decarbonisation, sustainable procurement compliance, and supply chain resilience. You will bridge the gap between unstructured sustainability disclosures and structured graph databases, building entity‑resolution pipelines that make enterprise data agent‑ready.

Your responsibilities will include (but will not be limited to):

• Graph Infrastructure and Ingestion Pipelines
  • Design, implement, and maintain high‑speed GraphRAG ingestion pipelines that transform relational data (ERP, SQL), unstructured ESG reports, and streaming feeds into operational Labeled Property Graphs (Neo4j, Memgraph) and RDF Triple Stores
• A‑Box Instantiation and Entity Resolution
  • Build automated Named Entity Recognition (NER), entity linking, and deduplication workflows to resolve mismatched vendor profiles, material SKUs, and facility coordinates into unified canonical graph nodes
• Semantic Federation and External Data Integration
  • Implement automated ETL/ELT pipelines to map and federate internal supply chain data with external, open‑source ontologies and registries (such as GLEIF for corporate ownership, W3C SSN/SOSA for IoT sensors, and Copernicus for geo‑hazard alerts, PROV‑O for data provenance)
• GraphRAG and Agent Tooling
  • Partner with AI/ML Engineers to build low‑latency GraphRAG retrieval layers—writing optimized Cypher and SPARQL queries, implementing NL2Query tools for agents, hybrid vector‑graph indexing pipelines, and Model Context Protocol (MCP) tool endpoints for autonomous LLM agents
• Deterministic Guardrails and Pipeline Validation
  • Operationalize SHACL (Shapes Constraint Language) shapes into automated data quality tests within CI/CD pipelines to prevent hallucinated or non‑compliant data mutations from entering the enterprise knowledge graph
• Performance Optimization and GraphOps
  • Optimize multi‑hop query performance, graph partitioning, and database indexing strategies to handle sub‑second traversal over billions of nodes and edges

Qualifications

• Degree in Computer Science, Mathematics, Engineering, or a related technical discipline
• 4+ years of production experience building and querying graph databases, specifically Labeled Property Graphs (Neo4j, Memgraph, TigerGraph) or RDF Triple Stores (GraphDB, Stardog, Virtuoso)
• Strong experience in cloud technology, preferably Azure and its ecosystem (e.g., Azure Foundry, Azure Bicep, AzureML and Azure Cloud Storage)
• Advanced proficiency in Python (RDFLib, NetworkX, PyGraphistry) for building scalable, production‑grade data pipelines
• Experience building entity extraction pipelines using modern NLP frameworks (LangChain, LlamaIndex, spaCy) or LLM‑based structured extraction
• Hands‑on experience with modern data transformation tools (dbt) and integrating graph databases with vector stores (Qdrant, Pinecone, pgvector) for hybrid search architectures
• Solid understanding of semantic web standards (RDF, RDFS and OWL, SKOS, SHACL, RDF‑star, SPARQL), graph schema design principles (T‑Box vs. A‑Box separation), and mapping languages for dealing with heterogeneous data structures (RML, R2RML)
• Experience working with domain‑specific supply chain, carbon accounting (GHG Protocol), or lifecycle assessment (LCA) data structures is a plus
• Direct experience building Model Context Protocol (MCP) servers to expose graph tools to LLM agents is a plus
• Experience with enterprise OBDA approaches at‑scale is a plus

Additional Information

• Offer available only for candidates eligible to work and live in Poland
• Location: Hybrid in Warsaw (4 days per month in the office) / Full remote from Poland

In return for your expertise, we offer:

• Support with all the necessary office and IT equipment
• Flexible working hours
• Wellness allowance for mental and physical wellbeing
• Access to professional mental health support
• Referral bonus policy
• Learning and development
• Sustainability events and community involvement
• Peer recognition program
• Employee‑led resource groups
• Optional (fully covered or co‑financed) health care and life insurance
• Multisport card
• Multikafeteria
• Lunch card
• Hybrid work organization
• Remote work from abroad policy
• Internet and Electricity bill allowance
• Additional day for community service when volunteering

We’re interested in hiring capable people, regardless of professional and educational background. We want everyone going through the hiring process with EcoVadis to feel confident that you are able to demonstrate your full potential. We welcome applications from disabled people, people with long‑term health conditions, and neurodiverse candidates. If you need any adjustments, including the provision of interview questions, please let the hiring team know. Our team’s strength comes from everyone’s uniqueness and is founded upon mutual respect. EcoVadis commits to equity, inclusion and reducing bias in our hiring processes. EcoVadis does not accept any form of discrimination based on color, national or ethnic origin, ancestry, citizenship, religion, beliefs, age, sex, gender identity, sexual orientation, neurodiversity, disability, parental status, or any other protected characteristic that makes you unique. In your application, we encourage you to remove personal information such as: photographs, marital status, number of children, religion, gender, residential postal code, university graduation date, past medical or parental leave(s) taken, nationality (instead, please state if you are legally eligible to work in the job region/country), university name (instead, please state any degrees obtained and the study major).