AI & Automation Engineer
- Hiring from
- Portugal
- Work type
- Hybrid
- Posted
603,685 remote jobs, straight from company career pages
100% free · New jobs every minute
Show job descriptionHide job description
Our office is near Porto, in the north of Portugal, and is located in a vibrant business hub. It offers a dynamic and welcoming environment where our employees can connect and network with a large community of tech professionals.
“How do you process millions of luxury product SKUs, unstructured brand attributes and high-volume media assets with speed, precision and low human friction?”
At Farfetch, our Catalogue and Content domain powers the digital storefront for the world’s leading fashion brands and boutiques. We are building the next generation of automated, AI-driven ingestion and enrichment pipelines. We aren't looking for someone to shoehorn LLMs into every problem, we need someone who knows when a deterministic Python script wins, when a workflow DAG is required and when a multi-step AI agent can accelerate our time to market.
WHAT YOU'LL DO:
Partner with stakeholders across Catalogue and Content, Product and Data to understand business problems, challenge existing processes, identify automation opportunities and translate them into practical solutions, from straightforward process automation to more complex AI-driven solutions;
Own the full development lifecycle from initial problem framing and prototyping to production deployment, monitoring and ongoing optimization, including system design, testing, evaluation and continuous improvement;
Build robust GenAI applications and LLM-based workflows leveraging RAG, structured outputs, function/tool calling, context management and multi-step reasoning workflows where appropriate;
Construct and orchestrate reliable backend services and pipelines using Python, Apache Airflow, APIs and cloud-native solutions, optimizing for system reliability, latency and inference/token costs;
Define and track operational metrics (throughput speed, error reduction, operational hours saved, metadata quality) to measure the tangible ROI of every deployed solution;
Establish reusable patterns, practices and capabilities for building reliable, maintainable and scalable AI and automation solutions, implementing AI safety best practices (prompt injection defense, guardrails, output validation);
Explore and prototype emerging AI capabilities, evaluating how they can solve real business problems and evolve into production-ready solutions;
Help shape and expand our AI practice into a fully formed capability and service offering for the Catalogue and Content domain, combining systems design, consulting, delivery, and innovation.
WHO YOU ARE:
Must have:
5+ years of relevant development experience (Software Engineering, MLOps, Applied AI, Automation or Data);
A pragmatic approach to technology: knowing when to use AI, conventional automation or neither;
Deep expertise in Python, SQL and designing clean, maintainable backend services/microservices;
Hands-on experience with workflow orchestration platforms (e.g. Apache Airflow) and webhooks/API integrations;
Strong practical knowledge of prompt engineering, vector databases/embeddings, RAG architectures and output validation frameworks (e.g., Pydantic, Instructor, Guardrails);
Familiarity with modern software delivery workflows: version control (Git), containerized applications (e.g., Docker) and basic cloud deployments;
Demonstrated experience with AI safety considerations: prompt injection defense, output validation and reliability engineering in production;
Ability to work across technical and business contexts and communicate effectively with non-technical stakeholders.
Nice to have:
Experience evaluating or building autonomous multi-agent frameworks (e.g., LangGraph, AutoGen, CrewAI);
Domain knowledge in e-commerce content operations, product taxonomy management or catalog enrichment systems;
Background in machine learning, NLP or computer vision architectures.
Ultimately...
We're looking for someone who can see an inefficient process, understand the underlying problem, figure out how it could work better and build the technology to make it happen.
Someone who can move fluidly between business problems, automation and data, and help us turn AI from a collection of solutions into a genuine capability within Catalogue and Content.