Company DescriptionWork 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 general 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 DescriptionWe 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. We welcome applications from European locations, with the possibility of remote work. Join us!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 PipelinesDesign, 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 StoresA-Box Instantiation and Entity ResolutionBuild automated Named Entity Recognition (NER), entity linking, and deduplication workflows to resolve mismatched vendor profiles, material SKUs, and facility coordinates into unified canonical graph nodesSemantic Federation and External Data IntegrationImplement 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 ToolingPartner 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 agentsDeterministic Guardrails and Pipeline ValidationOperationalize 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 graphPerformance Optimization and GraphOpsOptimize multi-hop query performance, graph partitioning, and database indexing strategies to handle sub-second traversal over billions of nodes and edgesQualificationsDegree in Computer Science, Mathematics, Engineering, or a related technical discipline4+ 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 pipelinesExperience building entity extraction pipelines using modern NLP frameworks (LangChain, LlamaIndex, spaCy) or LLM-based structured extractionHands-on experience with modern data transformation tools (dbt) and integrating graph databases with vector stores (Qdrant, Pinecone, pgvector) for hybrid search architecturesSolid 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 plusDirect experience building Model Context Protocol (MCP) servers to expose graph tools to LLM agents is a plusExperience with enterprise OBDA approaches at-scale is a plusAdditional InformationOffer available only for candidates eligible to work and live in SpainLocation: Hybrid in Barcelona (4 days per month in the office) / Full remote from SpainIn return for your expertise,



we offer:Support with all the necessary office and IT equipmentFlexible working hoursWellness allowance for mental and physical wellbeingAccess to professional mental health supportReferral bonus policyLearning and developmentSustainability events and community involvementPeer recognition programEmployee-led resource groupsRemote work from abroad policyMeals and Transportation Vouchers (Coverflex card)Dental BenefitsLife & Accident Insurance + Private Health InsurancePaid employee volunteer dayPaid moving day (1/year)Time off: 1 Community Service Day + 1 Personal DaySummer Hours in July and August (36 hours per week)Hybrid Monthly Allowance for electricity and InternetOur hiring team looks forward to reviewing your CV, in English, with a guaranteed response to every application. A new job with purpose awaits you!Don’t fit all the criteria but still think you’d be a good candidate? Please apply anyway to give our hiring team the opportunity to assess your skills and to learn more about what you could bring to EcoVadis. We’re interested in hiring from a diverse and skilled talent pool, regardless of professional and educational background.Can the hiring process be adjusted to suit my needs? Yes. 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).Our recruitment processes do not include AI systems that make autonomous decisions impacting individuals’ rights without human oversight. Inputs and outputs of the system have been validated by humans and answers are based on algorithms that analyze previous data with which the system has been trained. We use SmartRecruiters as our applicant tracking system and to schedule interviews. Gemini is used to summarize notes from interviews and to refine job descriptions and social media messaging. AssessFirst is used to support talent assessment decisions.#J-18808-Ljbffr

📌 Remote Senior Knowledge Graph Engineer — Ai Pipelines (Madrid)
🏢 Eco Vadis
📍 Madrid