AI Engineer

Pillar; Bellprat; On-site; EUR 55,000 - 75,000; Full time

Job summary

Pillar is hiring an AI Engineer to turn LLMs into reliable product experiences. You’ll own end-to-end AI features, design agentic workflows, and build RAG and semantic pipelines.

The role spans data, software, and product judgment, with collaboration across Product, AI and Engineering teams. You’ll work in a startup/scaleup setting, shipping real features for customers, with autonomy and growth opportunities.

Qualifications

• Experience building production-grade AI products, not only prototypes.
• Comfort with agents, tool use, structured outputs and orchestration.
• Hands-on with retrieval, embeddings, vector databases and retrieval strategies.
• Proficient in TypeScript or able to become productive quickly.
• Experience with AI orchestration frameworks such as Mastra, LangChain, CrewAI.
• Strong SQL and relational database skills.
• Understanding of prompt design and evaluation for reliable AI systems.
• Experience in startup or scaleup environments with high pace and ownership.

Responsibilities

• Own AI features end to end from problem to production.
• Design and build agentic workflows using tooling and multi-step reasoning.
• Build RAG and semantic search pipelines with embeddings and vector search.
• Develop document extraction workflows turning invoices and forms into data.
• Create observability and QA systems for AI features with tracing and experiments.
• Improve context, retrieval and prompting strategies for quality.
• Collaborate across our TS stack from backend logic to product integration.
• Move from ambiguity to working product with pragmatic decisions.

Skills

LLM-based apps

Agent orchestration

RAG and embeddings

TypeScript

SQL

LangChain

Mastra

Vector databases

Tools

Mastra

LangChain

CrewAI

Vector search

Job description

About Pillar

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'll 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

• Product: Next.js · React · TypeScript
• Backend & data: Supabase · Node/Deno · Postgres
• AI: Mastra · LLM APIs · embeddings · vector search · AI-native workflows

What You'll Bring

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 experience with RAG, embeddings, vector databases, and retrieval strategies.
• You are comfortable with TypeScript or can become productive in it quickly.
• You have worked with AI orchestration frameworks such as Mastra, LangChain, CrewAI, or similar.
• You are strong with SQL and relational databases.
• You understand prompt design, evaluation, and the trade-offs involved in building reliable AI systems.
• You have worked in a startup or scaleup environment and understand the pace, ambiguity, and ownership it requires.
• You take initiative, get your hands dirty, and get things done without waiting for perfect instructions.
• You can zoom out to understand the full product problem and zoom in when technical details matter.
• You communicate openly, learn quickly, and collaborate without ego.

How we work

• Agile and squad-based: small teams own their domains, with no unnecessary layers.
• AI-first: we build and work in the age of AI.
• Product ownership: engineers are hands-on and accountable for delivered value.
• Bottom-up: initiative is expected, not delegated.

The profile that can succeed

AI-native · Product-minded · Startup DNA

The sweet spot: a hands-on engineer who has already built real AI products, ideally in a startup or scaleup environment, and knows how to combine LLM capabilities, software engineering, data, and product judgment to ship reliable features.

Location & languages

Milan or Barcelona; professional working English is required regardless of location.

What we offer

• Gross salary 55,000-75,000 € depending on experience.
• The opportunity to build core parts of Pillar’s AI product and engineering foundations as we scale.
• End-to-end ownership: from AI architecture and experimentation to shipping features used by real customers.
• The chance to work in an AI-native engineering team, where AI is part of both the product and the way we build it.
• Close collaboration with Product, AI, and Engineering, with direct exposure to the problems we are solving for customers.
• Real autonomy, responsibility, and room to grow as Pillar and the engineering team scale.

Hiring process

1. CV screening.
2. 30-min Talent Call - motivation, Pillar knowledge, mindset, and startup fit.
3. Two 30-min Technical Interviews - one focused on AI systems and architecture, one focused on product engineering and execution.
4. Final Interview with our CTO.

One last thing

Pillar is hiring this person while all of that is still taking shape.

Build the system behind the scale.