happeo
happeo~3d ago
New

AI Engineer: Applied NLP & Knowledge Graphs

FinlandFinland·Helsinkimid
Machine Learning EngineerData
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Quick Summary

Key Responsibilities

extracting and structuring an organization's knowledge so issues in it can be detected. You'll ship from zero to production with minimal oversight and real autonomy to define the technical approach,

Technical Tools
Machine Learning EngineerData

Happeo is a Series B startup revolutionizing how organizations collaborate and communicate

through our unified social intranet platform. We combine collaboration tools, knowledge sharing,

and internal communications into one seamless solution that helps teams connect and stay

aligned. We pride ourselves on our dynamic, collaborative culture that emphasizes delivering

high-quality solutions while fostering professional development. No bureaucracy, just smart

people building things that matter.

About the Role

~1 min read

You'll be working with our development team to build Happeo's proprietary technology for

intranet information management. The platform helps organizations find gaps, duplication, and

outdated content, and keep the knowledge their teams rely on accurate and trustworthy. We're

launching into Open Beta, and the next frontier is knowledge that people, and the AI systems

they use, can actually trust.

This role builds toward Compass, Happeo's new knowledge verification layer. As AI systems like

Claude, Gemini, and ChatGPT increasingly answer from an organization's own knowledge,

Compass checks whether that knowledge actually holds up, surfacing where it's duplicated,

stale, or self-contradictory, and proposing fixes. The job isn't search, it's detection: you'll build

the knowledge graph and graph-RAG that understand what the knowledge says and whether it's

correct, not just which documents mention what.

React/React Native frontends, Python/Node.js/Java backends, running on GCP (App Engine,

Cloud Run, Kubernetes, Cloud SQL, Firestore, VertexAI).

Responsibilities

~1 min read

You'll stand up the knowledge graph and graph-RAG behind Compass from scratch; this doesn't

exist here yet, and building it is the job. It's novel work: extracting and structuring an

organization's knowledge so issues in it can be detected. You'll ship from zero to production with

minimal oversight and real autonomy to define the technical approach, make the architectural

calls, and drive direction. This isn't a detailed-specs role: you'll form opinions about what to

build, how, and why it matters, bring in knowledge the team doesn't have yet, and actively

spread it.

  • Build information extraction pipelines that turn messy documents into structured facts: entities and the relationships between them

  • Build claim extraction and entity resolution: pull atomic, verifiable claims from documents, and decide when two extracted things are the same entity

  • Detect where knowledge is duplicated, stale, or self-contradictory, and prove it works without crying wolf

  • Stand up the knowledge graph the detection runs on, and the graph-RAG layer that supports it alongside conventional RAG

  • Own the impact end to end: ship, measure, iterate, fail fast, learn faster

  • Evangelize what you bring in: level up the wider AI team so the knowledge sticks past you

The core of this role is applied NLP: turning messy, unstructured knowledge into verifiable

structure. That's where most of the work, and most of the difficulty, lives:

Nice to Have

~1 min read
  • Docker/Kubernetes

  • Java backend experience

  • Data engineering and ETL pipelines

  • DevOps/CICD experience (MLOps/LLMOps)

This role has a clear early bar, and it's an ambitious one. By day 90, success looks like:

  • A knowledge graph stood up and live in production: the foundation Compass runs its detection on, not a prototype

  • Working detection: Compass can flag where knowledge is duplicated, stale, or self-contradictory, with claims and entities resolved well enough to trust

  • Measured on precision and recall, not ranking: you're confident you're surfacing real issues, and just as confident you're not raising false ones

  • The wider AI team has learned something from how you built it: you've brought knowledge in and spread it

The home run is detection people trust: real issues caught, false positives kept low enough that teams act on what Compass tells them. The misfire is a clever graph that flags noise nobody believes. We're hiring for the first one.

This role is based in Helsinki, Finland. The working mode is Hybrid. If needed, we'll support you

with relocation and Visa application.

What We Offer

~1 min read
A competitive salary and equity plan
Flexible office setup with remote and hybrid working possibilities
Full 5-weeks holiday policy from day one
Comprehensive benefits, including healthcare, lunch, and phone subscription
Top-tier work equipment you need to succeed
A strong karaoke culture at practically every company event!

Location & Eligibility

Where is the job
Helsinki, Finland
On-site at the office
Who can apply
FI

Listing Details

First seen
June 15, 2026
Last seen
June 18, 2026

Posting Health

Days active
0
Repost count
0
Trust Level
51%
Scored at
June 15, 2026

Signal breakdown

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happeoAI Engineer: Applied NLP & Knowledge Graphs