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AI Engineer

Pubblicato il 17-10-2026 - Pillar in Milano

Pillar was founded in 2025. Today, we are 80+ people, serve 900+ customers, raised €12 million in 2026, and are expanding internationally.
We are building the financial operating system for construction: bringing AI, automation, and modern software to an enormous industry still full of slow, fragmented processes.
We are looking for an AI Engineer who knows how to turn LLMs into reliable product experiences, moves fast, and wants to build.
The mission Build production-grade AI systems that solve real customer problems.
We want someone who can move beyond prototypes and build agents, retrieval systems, document pipelines, and AI-native product features that are reliable, measurable, and deeply integrated into Pillar.
What you will do Own AI features end to end, from product problem to production.
Design and build agentic workflows using tool orchestration, structured outputs, and multi-step reasoning.
Build RAG and semantic search pipelines using embeddings, vector databases, hybrid search, and re-ranking.
Develop document extraction workflows that turn invoices, reports,



and forms into structured data.
Build observability and evaluation systems for AI features, including tracing, experimentation, and automated quality checks.
Optimize context, retrieval, and prompting strategies to improve accuracy and product quality.
Work across our TypeScript stack when AI features require it, from backend logic to product integration.
Use AI as a native part of your own engineering workflow, not only as something you build for customers.
Move quickly from ambiguity to working product, making pragmatic technical decisions along the way.
Our stack AI: Mastra · LLM APIs · embeddings · vector search · AI-native workflows
Who we are looking for AI engineers with product mindset and high agency You have experience building LLM-based applications in production, not only prototypes.
You are comfortable with agents, tool use, structured outputs, and orchestration.
You have hands-on experi

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