Mid-Level AI Engineer – Software Development & Machine Learning

Location: Porto, Portugal; hybrid work model. Only candidates with an existing legal right to work in the European Union will be considered.

Company

hirify.global is hiring for a technology client developing AI-powered features and intelligent automation solutions.

What you will do

• Design, develop, and deploy AI-powered features, including conversational AI modules, AI raters, and internal productivity tools.
• Integrate Anthropic, OpenAI, and other large language model APIs into scalable production applications.
• Optimize prompt engineering and RAG pipelines using Pinecone, Weaviate, and pgvector.
• Implement REST and GraphQL APIs, microservice architectures, and cloud solutions across AWS, GCP, and Azure.
• Write clean, tested, and efficient code while improving model performance through evaluation and analysis of failure modes.
• Communicate technical concepts and collaborate with senior engineers, product managers, designers, and other stakeholders.

Requirements

• 2+ years of professional software engineering experience, preferably with Python and/or TypeScript/JavaScript.
• Hands-on experience with language model APIs, prompt engineering, RAG pipelines, and vector databases.
• Familiarity with agent frameworks such as LangChain, LangGraph, LlamaIndex, or CrewAI.
• Experience with REST or GraphQL API design and at least one of AWS, GCP, or Azure.
• Basic understanding of ML fundamentals, embeddings, model evaluation, and model failure modes.
• Fluent English and an existing legal right to work in the European Union are required.

Nice to have

• Experience in Insurtech, Fintech, or other regulated industries.
• AI or Machine Learning certifications or additional expertise.

Culture & Benefits

• Hybrid work model in Porto, Portugal.
• Opportunities to work on conversational AI, productivity tools, and advanced AI integration projects.
• Use of AI-assisted coding tools such as Claude Code, Cursor, and GitHub Copilot.
• Continuous learning focused on ML fundamentals, model evaluation, and AI system limitations.