Database Engineer — Knowledge Graph Platform

At Mindboxwe connect top IT talents with technology projects for leading enterprises across Europe.

We are seeking a Database Engineer to design, build, and scale Knowledge Graph capabilities across the enterprise environment, driving integrated graph solutions and AI-enabled use cases. This role combines deep graph database expertise, cloud platform engineering on GCP, and LLM integration for advanced retrieval patterns such as RAG and GraphRAG.

If you have strong technical skills across LPG and RDF ecosystems, production-grade delivery experience, and passion for graph-powered AI workflows, this position is for you.

Sounds like your kind of challenge?

Responsibilities

• Flexible cooperation model
• Hybrid work setup - 8 times per month from the office
• Collaborative team culture - work alongside experienced professionals eager to share knowledge
• Continuous development - access to training platforms and growth opportunities
• Comprehensive benefits - including Interpolska Health Care, Multisport card, Warta Insurance, and more
• High quality equipment - laptop and essential software provided

Requirements

• Own the end-to-end graph platform lifecycle: architecture, deployment, reliability, and continuous evolution.
• Design graph schemas and ontologies across LPG and RDF paradigms, ensuring standards-based governance and version control.
• Build and operate scalable data ingestion pipelines (batch and streaming) with data quality and lineage frameworks.
• Implement robust observability and reliability practices aligned with SRE principles on GCP (monitoring, alerting, HA).
• Define engineering guardrails for performance tuning, query optimization, and cost-efficient scaling.
• Collaborate with product, data, and security stakeholders to deliver reusable platform services for internal teams.
• Activate AI-driven reasoning and retrieval scenarios leveraging LLMs, embeddings, vector databases, and hybrid GraphRAG workflows.

Note:Detailed project information will be shared during the recruitment process.

Benefits

• 3+ years in data/database engineering, including graph platform implementation.
• Experienced in both major graph ecosystems:
  • LPG stack: Cypher/Gremlin; platforms like Neo4j, FalkorDB, JanusGraph.
  • RDF stack: SPARQL; platforms like GraphDB, Stardog, Blazegraph, Neptune RDF.
• Proficiency in graph standards (RDF, RDFS, OWL, SHACL) and ontology governance/versioning best practices.
• Hands-on delivery experience on Google Cloud Platform (GCP) including GKE, Cloud Run, Pub/Sub, Dataflow, BigQuery, IAM, dashboards/monitoring.
• Practical LLM integration exposure (embeddings, vector/hybrid retrieval, GraphRAG workflows).
• Strong foundations in Python and/or Java/Scala/Node.js, API integration, CI/CD pipelines, and Infrastructure-as-Code (Terraform, GitOps).
• Proven track record in leading engineering efforts and delivering iterative platform roadmaps.
• Clear communication across technical and non-technical stakeholders, ability to translate business objectives into platform capabilities.
• Commitment to engineering excellence, proactive incident management, and continuous improvement culture.

Nice to have:

• Multi-tenant architecture and platform productization experience.
• Knowledge of responsible AI practices, model guardrails, and evaluation frameworks.
• Experience with Kubernetes operators and advanced observability stacks (Prometheus, Grafana, OpenTelemetry).
• Familiarity with FinOps strategies for high-memory graph workloads.

Joining this project you’llbecome part of Mindbox - a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’llback you up every step of the way, accelerate your development, and ensure your skills make a difference.