AI Engineer: Applied NLP & Knowledge Graphs at Happeo

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• 🏢 Happeo has 2 jobs here, 1 with visa sponsorship see all

Updated 2026-11-05, from our data and official sources.

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About the role

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.

Responsibilities

Build a knowledge graph and graph-RAG system from scratch to detect duplicated, stale, or contradictory information within organizational knowledge. Develop information extraction pipelines to turn unstructured documents into structured facts and verifiable claims.

Requirements

Requires strong practical experience in applied NLP, LLMs, and knowledge graphs using tools like Neo4j and Cypher. Candidates should have backend experience in Python or Node.js and be comfortable working with GCP and multilingual content.

Key skills

• Applied NLP — not in any other listing on The Stack
• Knowledge Graphs — in 2 other listings on The Stack
• Graph-RAG — not in any other listing on The Stack
• Information Extraction — not in any other listing on The Stack
• Entity Resolution — not in any other listing on The Stack
• Neo4j — in 1 other listing on The Stack
• Cypher — not in any other listing on The Stack
• Python — in 1200 other listings on The Stack
• Node.js
• GCP
• LLMs
• Natural Language Inference
• Ontology Development
• Taxonomy Development
• Backend Development
• Multilingual Content Processing

On The Stack (as of 2026-11-05)

• Happeo has 1 other listing on The Stack.
• 18 visa-sponsored ai engineer jobs in Europe on The Stack, posted in the last 60 days.

Frequently asked questions about Happeo

Is this AI Engineer: Applied NLP & Knowledge Graphs role still open?

It was posted on 2026-05-29. Listings more than 30 days old may no longer be active, so check Happeo's site before applying.

Does Happeo offer visa sponsorship?

This listing is marked as offering visa sponsorship. Eligibility rules are set by the employer, so check the details on Happeo's site.

Where is this role located?

The listing gives the location as Helsinki, FI, Finland. It is marked on-site.

What skills does this role ask for?

The listing names: Applied NLP, Knowledge Graphs, Graph-RAG, Information Extraction, Entity Resolution, Neo4j, Cypher, Python, Node.js, GCP, LLMs, Natural Language Inference, Ontology Development, Taxonomy Development, Backend Development, Multilingual Content Processing.