[Hiring] Forward Deployed AI Engineer @Tuio

Role Description

¿Cómo será tu día a día en Tuio?

• You will work directly with business teams to understand the processes, decisions, systems, data, exceptions, and risks involved in each use case.
• You will design the architecture of agent-based systems, selecting the most appropriate models, patterns, and components for each problem.
• You will build applications powered by language models using context engineering, tool calling, structured outputs, RAG, and multi-step workflows.
• You will experiment with models, instructions, and architectures to optimize the balance between quality, latency, cost, and reliability.
• You will connect agents to internal and external tools through APIs, MCP servers, databases, and SaaS platforms.
• You will rapidly create prototypes and evolve them into solutions used with real-world data, systems, and use cases.
• You will design evaluations, test cases, and regression tests, and instrument agents to monitor their traces, errors, latency, and costs.
• You will implement reliability and control mechanisms such as permissions, validations, retries, fallbacks, action limits, and escalation to a human.
• You will deploy and operate solutions using testing, version control, CI/CD, and sound engineering practices.
• You will turn the lessons learned from each deployment into reusable components, evaluations, and patterns for future Tuio agents.
• You will become embedded in one of Tuio’s priority domains to understand its processes, systems, and key technical challenges.
• You will take responsibility for one or two use cases and bring at least one of them from prototype to a pilot with real users, defining its evaluations, observability, and next steps for scaling.
• Your day-to-day work will combine close collaboration with the business, end-to-end technical ownership, and a way of building based on experimenting quickly, measuring rigorously, and strengthening controls whenever the level of risk requires it.
• You will be involved from the discovery stage and work directly with the people who understand and operate each process.
• Depending on the project, you will collaborate with AI Managers and colleagues from Business, AI, Data, and Engineering to define and evolve the solution.
• You will take end-to-end technical ownership, including AI architecture, code, integrations, evaluations, deployment, observability, and reliability.
• In some projects, you will also play a significant role in discovery and functional design.
• You will build small initial versions to validate hypotheses with real users, measure outcomes, and iterate quickly.
• We will consciously accept technical debt when it helps us learn, but we will strengthen the architecture, testing, and security before scaling.
• You will treat agents as production systems: you will version instructions, tools, and evaluations; analyze traces and failure modes; measure quality, latency, and cost; and test every change against representative cases.
• You will adapt the speed of development and level of control to the degree of risk.
• In low-risk cases, you will experiment with a high level of autonomy.
• In more sensitive processes, you will introduce permissions, traceability, validations, action limits, data isolation, and human oversight.
• You will turn the lessons learned from each project into reusable components, evaluations, and patterns, helping make every new agent faster and more reliable to build than the previous one.
• The goal will not simply be to launch a demo, but to demonstrate that an agent can improve a real-world operation in a measurable, reliable, and responsible way.

Qualifications

• A university degree in Engineering, Mathematics, Physics, or another related scientific, technical, or quantitative discipline.
• At least five years of experience in AI Engineering, Applied AI, Software Engineering, Product Engineering, Data, or a similar technical role.
• A strong programming foundation, particularly in Python.
• Experience building applications with language models and an understanding of concepts such as context engineering, tool calling, structured outputs, RAG, evaluations, and human-in-the-loop systems.
• Experience working with APIs, databases, authentication, testing, Git, and cloud-deployed services.
• The ability to turn an ambiguous problem into an architecture and an initial implementation without needing a fully finalized specification.
• The ability to use data, metrics, traces, and evaluations to analyze and improve the behavior of an AI system.
• Strong engineering judgment when balancing quality, latency, cost, security, maintainability, and development speed.
• An interest in working closely with users and the ability to communicate clearly in English with both technical and business stakeholders.

Requirements

• Experience deploying agents or language-model-based products used by real users.
• Experience with tool calling, RAG, MCP servers, vector databases, workflows, or agent architectures.
• Experience building evaluation, observability, monitoring, or human-in-the-loop systems for AI applications.
• Knowledge of cloud infrastructure, containers, CI/CD, queues, or event-driven architectures.
• Experience using AI-assisted development tools to build, test, and maintain software.
• Experience working with sensitive data, access controls, traceability, or AI systems in regulated environments such as insurance or insurtech.

Benefits

• Competitive salary based on your experience and expertise.
• Flexible working hours: we do not believe in enforcing a rigid 9:00 a.m. to 6:00 p.m. schedule.
• Remote work: although, should you feel like coming into the office, we are based in Madrid!
• A growth plan within a rapidly expanding company.
• The opportunity to work at a company where AI is not a trend, but a fundamental part of how we build products and improve our work every day.
• The opportunity to build solutions with real impact: you will work on real operations and use cases, not isolated demos.
• Top benefits: flexible compensation, health insurance, Tuio insurance policies, home-office equipment, team-building events, and much more.

Selection Process

If you like what you have read, apply directly. Should you also like to tell us a little more about yourself, email us at [email protected].

• A conversation with our Head of AI & Data, who will explain the project, the team, and the challenges of the position.
• A video call with the People team—we promise not to ask you about your strengths and weaknesses.
• A conversation with our co-founder in charge of AI Deployment.
• A practical case in which you will need to understand an operation, identify an opportunity, and build or propose an initial agent-based solution.
• A review of the case with the AI & Data team, including the decisions you made, the experiments you carried out, the metrics you used, and the risks you identified.

Welcome to the team!