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AI Engineer, Product - Milan

indigo.ai•Italy•🌍 Remote
Full-timeMid Level
€38K - €45K
per year
👁️ 0 views•📝 0 applications•Posted 10/27/2026•Expires 12/26/2026
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Job Description

If you are here, it is because you know that we are looking for a AI Engineer for our Product team. indigo. ai is the leading platform in Italy for building next-generation AI Agents that transform the way companies communicate with their customers.

Since 2016, we’ve been helping enterprises in industries such as finance, insurance, utilities, retail, and e-commerce to evolve their Customer Experience through conversational AI.

We don’t just “sell software”: we enable a shift in how organizations interact with people, automating millions of conversations every year, reducing operational costs, improving conversion rates, and creating more personalized, scalable, and compliant customer journeys.

Backed by a recent €10 million investment from Azimut, we are on a mission to take this technology global. This is a unique opportunity to join a well-funded, highly ambitious team and play a direct role in shaping the future of enterprise AI.

To make this happen, we are looking for a Product AI Engineer to and work alongside the person who leads AI on the product today. What are we looking for? We are looking for an AI Product Engineer to join our Product team. This role combines software engineering fundamentals, product sense, and hands-on AI execution.

You will own AI features end-to-end—building agentic workflows, designing RAG architectures, establishing evaluation pipelines, and integrating probabilistic AI systems cleanly into our platform.

Key Responsibilities

End-to-End Feature Delivery: Design, prototype, and ship AI capabilities directly into the product, owning features from initial concept to production deployment.

Agentic Pipelines & Workflows: Build multi-step agentic workflows, tool-calling frameworks, and decision-making logic that reliably orchestrate complex enterprise tasks.

RAG & Knowledge Architectures: Design and optimize Retrieval-Augmented Generation (RAG) architectures over messy enterprise documents, tuning search strategy, context retrieval, and r

Required Skills

AIsoftware engineeringproduct senseagentic workflowsRAG architecturesevaluation pipelinesprobabilistic AI systems

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