About the Position

AI Engineer (LLM Systems in Production)

Engineering

Aveiro, Portugal - Hybrid

Hybrid Model

Modern office with remote flexibility

Ownership & Autonomy

Own your metrics and your impact

Team Building

Regular meetups to connect and celebrate

Great Culture

The best ideas come over coffee chats

About the Role

At miio we’re building the simplest way to charge an electric vehicle. Our AI squad builds and runs the LLM systems behind that experience: the agent that reads, classifies and answers customer support tickets, the assistant our support team works alongside, and the tools and data services those agents depend on. These systems run in production, against real customers, every day. You’ll join a small, high-ownership squad and take end-to-end responsibility for agent features: from understanding the problem and designing the pipeline, through the PR and review, to watching it behave in production and fixing what the traces show. Nobody hands you a fully specified ticket and nobody reviews your work into shape for you. This is a hands-on engineering role, not a research or prompt-writing one. Most of the difficulty is in the system around the model: the tool-calling loop, the guardrails, the failure handling, the data contracts between services, and knowing whether the thing actually works.

Responsibilities

Build and ship agent features in production: orchestration graphs, tool-calling loops, retrieval over our knowledge base, and the services behind them
Own the guardrails and failure paths, so the system fails safely and hands off to a human instead of answering wrong
Design and maintain the backend services and integrations the agents depend on, across several repositories and their contracts
Instrument what you ship and use traces, logs and metrics to decide what to change next, rather than guessing
Evaluate agent quality with real data: build the measurement before claiming the improvement
Review your squadmates’ code critically and take critical review of your own without friction
Work directly with the support and product teams to turn real customer problems into system changes

Requirements

2+ years of professional backend engineering in Python, with production ownership of what you shipped
Hands-on experience building LLM-powered features that reached real users: tool/function calling, retrieval, structured outputs, or agent loops
Solid API and data fundamentals: REST design, relational data modeling, asynchronous and queue-based processing
Comfortable debugging production systems from logs and traces, forming a hypothesis and proving it
A habit of validating your own output: tests, evaluations, and healthy skepticism about results that look good
Able to work with ambiguity and drive a task to done without close supervision
Fluent English (written and spoken)

Nice to Have

Django / DRF, FastAPI, Celery or equivalent task queues
Agent frameworks (LangChain / LangGraph or similar), vector databases, and the Model Context Protocol
LLM observability and evaluation tooling (Langfuse, or your own equivalent)
Experience with prompt injection, PII handling or other AI safety and privacy concerns in production
Fluent use of AI coding assistants in your daily workflow, with the judgment to verify what they produce
Interest in EVs, energy or sustainability

We Offer

Competitive salary aligned with your experience
24 days of vacation
Hybrid work model with a modern office in Aveiro
Health insurance
Real ownership over systems that talk to customers every day, in a squad small enough that your decisions matter

Interview Process

Intro call & Technical interview with the AI team lead (60 min)
Take-home challenge, time-boxed to a few evenings
Review session where you walk us through your solution and make a small live change to it
Final conversation with the team lead, CTO & CPO

AI Engineer (LLM Systems in Production)

Job description