Recevez plus de réponses des employeurs
Envoyez un CV adapté au poste en quelques minutes.
Carbonfact is hiring a Software Engineer to join the LCA team in Paris. You will build and scale the engine that turns supplier and product data into environmental footprints, collaborating with science, data, and engineering colleagues.
You will ship features in short cycles, contribute to a rigorous model, and interact with customers to explain results. Experience with TypeScript and fullstack delivery is required, and relocation to Paris is encouraged.
The fashion industry is responsible for 5–10% of global greenhouse gas (GHG) emissions. As pressure for climate action grows, more companies are turning to carbon management tools. But most platforms are generic, lacking the depth needed for driving real change in fashion.
That's why we built Carbonfact, the only environmental data platform tailored for the textile and fashion industry. Our platform automates product-level life-cycle assessments (LCAs) and company-level carbon accounting, helping brands measure, model, and reduce their impact with precision.
We've raised $17M from top-tier investors including Alven, Headline, and Y Combinator, and we're already trusted by leading brands like Carhartt, GANNI, On, Burton, Armedangels, Jack Wolfskin, and many more.
As a Software Engineer on our LCA team (led by Leonardo), you'll build and scale the engine that turns raw supplier and product data into environmental footprints. It already computes more than 2 million LCAs per day, and our ambition is to make it the most scalable LCA engine in the world.
The LCA team sits at the intersection of our science, data, and engineering teams. You'll turn methodology into code with our scientists, work on the pipelines that feed the engine with our data team, and ship the results to customers with the rest of engineering. You'll also talk directly to our most advanced customers and prospects, who want to understand exactly how a number was produced.
The LCA team is directly responsible for the calculations, ensuring trust with our customers. Every footprint we publish ends up in a customer report, a regulatory filing, or a product page. That asks for a high level of rigor: in how we model, how we test, and how we explain our results.
Our engineering team is lean, autonomous, and product-focused.
We work in 5-week cycles following the Shape Up method, with 1 cooldown week for tech debt and loose ends.
During cycles, we focus on delivering bets - projects with a set time appetite. Engineers own both project management and delivery autonomously, with peer support.
Every day, our software engineers write Typescript, SQL, and more rarely dig into some Python code for the parts of our infra we share with our Data team.
We use:
We deploy on Google Cloud, Vercel and Cloudflare, using infrastructure-as-code (terraform). We are well equipped with various tools to speed us up and handle the busy-work for us: Sentry for monitoring, Cubic for AI code reviews, Aikido for security scanning, etc.
We believe that AI will play a major role in software development and operations, and we leverage the latest technologies to help us achieve more with less. Our team is empowered with generous access to the best tools on the market, and we build and exchange skills and best practices both within the engineering team and across the whole company.