Database Engineer — Knowledge Graph Platform

At Mindbox we 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?  

What you get in return

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

Daily tasks

• 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.

Requirements

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

Must have: Gremlin, Neo4j, SPARQL, Google Cloud Platform, Cloud, PUB, BigQuery, IAM, Python, Java, Scala, Node.js, API, CD pipelines, Terraform

Nice to have: AI, Kubernetes, Prometheus, Grafana