AI & Automation Engineer

Location: Hybrid in Porto, Portugal

Company

hirify.global operates a digital fashion marketplace for leading luxury brands and boutiques.

What you will do

• Partner with Catalogue and Content, Product, Data and Operations stakeholders to identify bottlenecks and translate business problems into automation and AI solutions.
• Own the full lifecycle from problem framing and prototyping through production deployment, monitoring, testing, evaluation and optimization.
• Build GenAI applications and LLM workflows using RAG, structured outputs, function and tool calling, context management and multi-step reasoning.
• Build and orchestrate backend services and pipelines with Python, Apache Airflow, APIs and cloud-native solutions, optimizing reliability, latency and inference costs.
• Define operational metrics covering throughput, error reduction, hours saved and metadata quality, and establish reusable scalable engineering patterns.
• Implement AI safety practices including prompt-injection defense, guardrails and output validation, while helping develop an AI capability for Catalogue and Content.

Requirements

• 5+ years of relevant development experience in Software Engineering, MLOps, Applied AI, Automation or Data.
• A pragmatic approach to choosing AI, conventional automation or neither based on the problem.
• Deep expertise in Python and SQL, including clean, maintainable backend services and microservices.
• Hands-on experience with workflow orchestration platforms such as Apache Airflow and webhook/API integrations.
• Strong practical knowledge of prompt engineering, vector databases, embeddings, RAG architectures and output-validation frameworks such as Pydantic, Instructor or Guardrails.
• Familiarity with Git, containerized applications such as Docker and basic cloud deployments.
• Experience with AI safety, including prompt-injection defense, output validation and production reliability engineering.
• 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 such as LangGraph, AutoGen or CrewAI.
• Domain knowledge in e-commerce content operations, product taxonomy management or catalogue enrichment systems.
• Background in machine learning, NLP or computer vision architectures.

Culture & Benefits

• Health insurance for the whole family and additional well-being resources.
• 25 days of annual leave, plus two Caring Days per year.
• Boomerang sabbatical program after five years of service.
• Training opportunities and free access to LinkedIn Learning.
• Flexible benefits and a flexible working environment.