> Markdown version of [/jobs/ext/2020719-ops-ai-platform](https://www.wearedevelopers.com/jobs/ext/2020719-ops-ai-platform). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Ops AI Platform

- **Company:** Every Alaner
- **Location:** Spain (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Software Quality, DevOps, Machine Learning, Systems Architecture, Large Language Models, Multi-Agent Systems, Backend, AI Platforms
- **Published:** August 11, 2026
- **Apply:** https://es.trabajo.org/oferta-4112-3763a11965df323b2d8bd8c308f4f481

## About the Role

automate operational tasks at scale: prompting, tools configuration, testing, datasets, replayability, evaluations Build a complete set of tools made available to AI agents, connecting to internal and external capabilities: internal business data, external servers, external web dashboards without API, etc. Safety and accuracy at the core: robust testing, stateful evaluation, progressive rollout, human-in-the-loop to validate sensitive actions, fine-grained permissions and limits In 6 to 12 months, we plan to increase our scope by owning the AI platform that will power all agentic use cases at Alan - creating economies of scale thanks to common infrastructure and tooling. If you're excited by the idea of building the future of work, this is the team for you - we're at the start of the journey. Is it you we're looking for? We're looking for Product engineers with 3+ years of experience who get excited about building state-of-the-art AI systems
and applying them to real-world, high-stakes problems in operations. You'll work at the frontier of LLMs, tool calling, human-in-the-loop, internal tools UX, multi-agent architectures, and see your work deployed in production, used by our ops team You'll implement new capabilities for AI agents, as well as tooling to make ops autonomous on the creation, evolution, monitoring and evaluation of their agents You'll work on making our system scale, going from a few dozen to tens of thousands of tasks automated daily You'll have significant influence on system architecture and code quality You'll mentor engineers, contribute to our product & engineering culture, and help build the team (including participating in hiring). You would be a good fit at Alan if most of this sounds like you: Strong background in full-stack software engineering, systems architecture, with a spike in back-end engineering. Experience with traditional ML, or LLMs, or ML dev ops is a
big plus Product-minded: you want your solutions to be used, and impactful Self-directed and pragmatic Humble and still willing to grow (no matter your seniority) Collaborative, enthusiastic about teamwork, learning, and teaching Fluent in English (no need to speak French) But above all, we are looking for high potential and curiosity: make sure to show us this when you apply Everything else is a bonus. For this opportunity, we are aiming to hire within the D-F level range. Perks & Benefits At Alan, we believe that being in good health is a basic need, and it starts with our employees. This is why Alaners are provided with a stimulating environment and perks ensuring they are happy, efficient and spend only high-quality time with co-workers. Therefore, we offer: Fair rewards. Generous equity packages complement your base salary. Flexible Office. Amazing office space at our HQ, sponsored co-working hubs or a full-remote experience with home office equipment

## Description

excites you, this is it. Our north star We're building ops agents that work reliably and safely, without putting the engineering team on the critical path. Skills You'll work at the intersection of product engineering and ML engineering. Our mission is to create the platform that enables building accurate and reliable AI agents, delivering an outstanding experience to our internal Ops team for the creation, iteration and monitoring of their agents, without requiring hard technical skills. Things we're working on: Integrate agents at the heart of internal tools - UIs where Ops monitor and take action on concrete business situations. We want AI agents to become first-class citizens in this ecosystem, with context-aware chat modals, allowing users to review agents' reasoning, actions, and provide follow-up instructions - with instant impact on business data. Empower non-technical users to become autonomous in the creation and maintenance of agents to