AI Engineer: Applied NLP & Knowledge Graphs at Happeo

Helsinki, FI

on-site · full_time · Visa sponsorship

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Responsibilities:
- Design and build a production knowledge graph and graph-RAG layer (Compass) from scratch.
- Develop information-extraction pipelines to convert messy documents into structured entities, relationships and verifiable claims.
- Implement claim extraction and entity resolution to deduplicate and canonicalize knowledge items.
- Detect and surface duplicated, stale or self-contradictory knowledge with measurable precision and recall.
- Integrate graph-RAG with existing RAG systems and deploy pipelines on GCP (Cloud Run/Kubernetes/VertexAI as needed).
- Own end-to-end delivery: ship, monitor, measure impact, iterate quickly, and evangelize solutions across the AI team.

Requirements:
- Strong applied NLP experience (information extraction, NER, relation extraction, claim detection) in production systems.
- Hands-on experience with knowledge graphs (Neo4j or equivalent) and building graph-based RAG solutions.
- Backend development skills in Python or Node.js (Java experience acceptable) and familiarity with GCP services (VertexAI, Cloud Run, Cloud SQL, Firestore).
- Practical experience using LLMs in pipelines and understanding of multilingual content processing.
- Experience with entity resolution, verification techniques and engineering for precision/recall trade-offs.
- Proven ability to work autonomously, make architectural decisions, and teach/scale knowledge across teams.
- Startup mindset: comfortable shipping from zero to production and iterating based on metrics.