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EcoVadis is seeking a Senior Knowledge Graph Engineer to join its AI Center of Excellence. You will operationalize formal domain ontologies into high-throughput, multi-hop knowledge graph systems that power autonomous AI agents solving complex sustainability challenges—including decarbonization, sustainable procurement compliance, and supply chain resilience.
Key responsibilities include:
**Graph Infrastructure and Ingestion Pipelines**: Design 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.
**Entity Resolution and A-Box Instantiation**: Build automated Named Entity Recognition (NER), entity linking, and deduplication workflows to resolve vendor profiles, material SKUs, and facility coordinates into unified canonical graph nodes.
**Semantic Federation and External Data Integration**: Implement ETL/ELT pipelines to map and federate internal supply chain data with external ontologies and registries (GLEIF, W3C SSN/SOSA, Copernicus, PROV-O).
**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, hybrid vector-graph indexing, and Model Context Protocol (MCP) tool endpoints for autonomous LLM agents.
**Data Quality and Validation**: Operationalize SHACL (Shapes Constraint Language) shapes into automated data quality tests within CI/CD pipelines to prevent hallucinated or non-compliant data mutations.
**Performance Optimization**: Optimize multi-hop query performance, graph partitioning, and indexing strategies to handle sub-second traversal over billions of nodes and edges.
The role is hybrid (2 days/week in Warsaw office) with full remote option from Poland.
**Requirements:**
- Degree in Computer Science, Mathematics, Engineering, or related technical discipline
- 4+ years of production experience building and querying graph databases (Labeled Property Graphs: Neo4j, Memgraph, TigerGraph; or RDF Triple Stores: GraphDB, Stardog, Virtuoso)
- Strong cloud technology experience, preferably Azure ecosystem (Azure Foundry, Azure Bicep, AzureML, Azure Cloud Storage)
- Advanced Python proficiency (RDFLib, NetworkX, PyGraphistry) for 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
- Solid understanding of semantic web standards (RDF, RDFS, OWL, SKOS, SHACL, RDF-star, SPARQL), graph schema design (T-Box vs. A-Box), and mapping languages (RML, R2RML)
**Preferred qualifications:**
- Experience with domain-specific supply chain, carbon accounting (GHG Protocol), or lifecycle assessment (LCA) data structures
- Direct experience building Model Context Protocol (MCP) servers for LLM agents
- Enterprise OBDA (Ontology-Based Data Access) approaches at scale
Candidates must be eligible to work and live in Poland.
