Founding Engineer - Avery

Builders Studio is a startup studio that partners with bold founders to build stellar enterprise AI and software companies from day zero and beyond. They provide firepower, network, and on-the-ground execution to turn big ideas into industry-defining companies, focusing on the future of work through AI.

Founding Engineer role at Avery, a Hiring Intelligence Engine backed by Builders Studio. Responsibilities include building ETL pipelines, full-stack AI-powered features, and predictive hiring models using millions of candidate profiles and market data across Europe.

Job Description

About Avery

Avery is a Hiring Intelligence Engine - not another Applicant Tracking System (ATS) or sourcing tool, but a system that learns how your company hires and gets smarter with every role filled. We sit on millions of candidate profiles, hiring signals, and market intelligence data across Europe.

Our mission: make mis-hires as rare as accounting errors.

We're backed by Builders Studio, based in Rotterdam, and growing fast. Soon we'll move to Amsterdam.

Why this role exists

One of our founding engineers has moved on - we're looking for the person who fills that seat and raises the bar. We have real data. Millions of candidate profiles, hiring outcomes, market signals. What we don't yet have is someone obsessed enough to make that data do everything it's capable of - reliable pipelines, labeled datasets, and eventually, predictive models that tell a company who to hire before they even know they need someone.

What you’ll build

Data Analysis & Engineering (50%)

• Build and own ETL pipelines that make our candidate, hiring, and market data reliable, accessible, and production-ready
• Dig into the data - surface patterns, catch quality issues, find what's missing
• Establish data quality standards and monitoring so everything downstream is built on a trustworthy foundation
• Identify data gaps and either acquire what's needed or make the case for it

AI-Powered Platform (30%)

• Build full-stack features from backend logic to polished UI - we ship things people actually use
• Architect for scale: clean, well-tested, maintainable code that doesn't become tomorrow's problem
• Improve the agentic workflows powering our sourcing, screening, matching, and market intelligence systems
• Bring engineering judgment into product and UX decisions - you'll have a seat at that table

Predictive Hiring (20%)

• Define what labeled datasets look like for our domain - what does "good match" actually mean in data terms?
• Assess whether our data can support predictive models: candidate-role fit, response likelihood, time-to-fill
• Where the data supports it, build and iterate on fine-tuned models end-to-end - from exploration to production
• Own the data & AI roadmap alongside the interim CTO/CPO

Job requirements

What we're looking for

Must-haves

• Strong data engineering background: ETL pipelines, data infrastructure, analysis at scale
• Full-stack ability: comfortable across React, TypeScript, Next.js, Node.js - not just notebooks
• Hands-on AI/ML: LLMs, embeddings, RAG, fine-tuning, prompt engineering
• Data science fluency: statistical modeling, building labeled datasets, knowing when data can and can't support a model
• Familiarity with: OpenSearch, Apache Spark, AWS, Inngest, Railway, Mastra or similar agentic frameworks
• Uses AI-assisted development tools (Claude Code, Codex, etc.) as a matter of course

The mindset that matters more than the stack

• Gets excited about messy data - finding signal where others see noise
• Ships. Doesn't wait for perfect conditions
• Thinks in products, not just systems - cares whether what gets built actually helps someone
• Comfortable with ambiguity and building in an early-stage environment where the roadmap evolves
• Real data, real problem: Millions of profiles, genuine hiring signal, a clear path from data to prediction - this isn't a greenfield project with fake data.
• Founding-level influence: Technical direction, data strategy, product decisions - you'll shape all of it.
• Equity-first: Substantial equity for someone who wants to build long-term value, not just collect a salary.
• Competitive salary: Equity is the focus, but the package is fair.
• Something worth building: Companies make better hires. People land better roles. The impact is real.