AI Engineer (Python) — Build Real-World Climate AI

What if your code directly accelerated the climate transition?

At Tapio, we are building a SaaS platform that helps companies measure and reduce their CO₂ emissions.
Until now, much of this work has been manual: data collection, categorization, matching with emission factors, reporting.

👉 Today, AI is a complete game-changer.
And that's where you come in.
We are looking for someone to transform complex processes into simple, fast and scalable systems.

In concrete terms, you will:

• Designing RAG systems to match the right emission factors

• Extract and structure data (e.g. financial reports → carbon data)

• Build recommendation systems (emission factors, solutions, etc.)

• Integrate LLMs into the product in a reliable and scalable way

• Set up the infrastructure (pipelines, vector DB, monitoring, etc.)

• Iterate quickly, test, improve and ship useful features

The objective is simple: to automate as much as possible to allow our carbon experts to focus where they really create value.

You work on concrete things.
Features used.
With a direct impact.

• Solid software engineer (mid to senior)

• Very comfortable with Python and backend systems

• Hands-on experience with LLMs (APIs, RAG, agents...)

• You've already built things in production, not just POCs

• You can demonstrate that you have already used AI to create real value (automation, product features, performance gains, etc.)

You are someone who:

• likes to build useful solutions, not just "technically interesting"

• understands quickly and adapts in a rapidly changing environment

• is pragmatic, structured and impact-oriented

• takes initiative and moves the issues forward

We are looking for a builder. Someone who likes to ship.

Bonuses:

• Experience with LangChain (or equivalent), vector DB, data pipelines

• Knowledge of data issues / information structuring

• A first screening

• An exchange with HR to understand your background and your way of working

• A practical case or technical discussion based on concrete problems

• Meeting with the founders for final validation.