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A next-generation AI automation firm based in Barcelona is seeking a dedicated DevOps / Infrastructure Engineer. This foundational role involves managing all cloud infrastructure across AWS, GCP, and Azure while optimizing AI systems and maintaining high reliability. The ideal candidate will have 8 years of experience in fast-paced environments and expertise in Kubernetes, CI/CD pipelines, and AI applications. Join a team where your contributions have direct visibility in production and work closely with founders and engineering leaders.
Yuma is building a next‑generation orchestration platform that deploys autonomous AI agents dedicated to customer support in e‑commerce.
We already support 150 paying merchants and help them automate up to 80% of their customer tickets, freeing human agents for higher‑value conversations.
Founded by Guillaume Luccisano (3rd‑time YC founder) at the end of 2022, Yuma is one of the leaders in the AI Support Automation space with 10 consecutive months of double‑digit growth.
We are now a team of 25 passionate and ambitious people based between Paris, Barcelona and Boston and have grown revenue 5× in 2025. We aim to repeat this trajectory in 2026. The scale‑up phase is fully underway.
This is a foundational role. You will be our first dedicated DevOps / Infrastructure Engineer and will take full ownership of everything related to cloud infrastructure deployments, reliability and scaling.
Our engineering team is made up of 7 people, operates with intensity and moves fast. Rapid iteration is one of our biggest advantages. Over the past two years we’ve built a tremendous amount but the surface area ahead of us is even larger as we scale usage models and automation. You will play a key role in keeping our platform fast, reliable and ahead of the curve.
This role goes beyond DevOps. You will also contribute at the LLM layer: running evaluations, experimenting with models, improving latency, optimizing costs and helping shape how our AI systems operate at scale. If you enjoy working at the intersection of infrastructure backend systems and AI, this is exactly the kind of role where you’ll thrive.
Infrastructure & Platform
Backend & Data Systems
AI / LLM Systems
You have 8 years of experience in DevOps / infrastructure roles, ideally in fast‑paced SaaS or startup environments. You’ve scaled production systems before and know how systems behave under real load.
You’re equally comfortable deep in Kubernetes or writing Ruby / Python for a quick script tool or LLM eval. You care about reliability, speed and pragmatism. You enjoy working on AI systems and have hands‑on experience with LLM‑powered applications.
If you’re earlier in your career but have strong infrastructure experience and clear upside and you can reasonably grow into the full scope within 2 to 3 years, feel free to reach out. Raw talent is welcome but depth of experience scaling systems is a big plus here.
High impact with ownership from day one: join a small international engineering team where every feature you ship and every solution you design is directly visible in production.
Competitive compensation based on experience and stock options.
Fast growth fast learning curve: in this hybrid engineering role you’ll quickly gain exposure to AI product iteration, customer workflows and cross‑functional problem‑solving.
Work closely with founders and product / engineering leadership: your ideas and ownership will directly influence the roadmap.
A culture of ownership, transparency and continuous improvement: we move fast, iterate constantly and empower people to grow.
Flexibility: fully remote in Europe with preference for Barcelona office (Boston office is also an option).
Please, if you are considering applying, first read our culture page.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.