AI role · Open offer

Lead Applied AI Engineer — Location-aware assistants

Focus: Geospatial AI · Earth observation · Location intelligence

Geospatial intelligence & AI — satellite, mapping, and location-aware products

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Hybrid
Location: 52 Boulevard de Sebastopol, Paris, IDF 75003, France
Compensation: EUR 98k-124k/year + bonus
Experience level: Lead
Team: Applied AI & copilots
Benefits & perks

About this role

What the team is looking for and how this position fits.

Geoox is hiring a Lead Lead Applied AI Engineer — Location-aware assistants on the Applied AI & copilots team (Hybrid · Paris, France). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Geoox — Ship LLM-powered copilots grounded in maps, parcels, and operational telemetry. You will design retrieval over geo corpora, tool-calling for spatial queries, and safety reviews for user-facing answers.

Expectations: production prompt/version control, offline eval sets with geo-specific edge cases, and tight loops with design and legal on disclosure.

Company: https://www.geoox.com.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
OpenAI API

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

Vector DBsTool
Embedding storage, hybrid search, and freshness strategies for RAG and semantic retrieval.
PostGISTool
Regular use of PostGIS in the LLM & generative AI stack—configuration, debugging, and team conventions.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Share one example of grounding or guardrails you implemented for a domain-specific assistant.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, OpenAI API, TypeScript, and Vector DBs.
You have led LLM & generative AI initiatives across teams—setting technical direction, review standards, and rollout plans others could follow.
You are comfortable with the hybrid rhythm (Hybrid · Paris, France)—onsite collaboration when it matters, deep work when remote.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.

Apply

Candidate accounts only: add your headline and bio on , and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Share one example of grounding or guardrails you implemented for a domain-specific assistant.

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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Top skills

Python

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