Finance & AI Onboarding Intern

Why this role exists

At Cortena, we're building the AI execution layer for finance operations in SMEs. We have paying clients, real workflows running in production, and a product that is evolving fast.

New clients rarely arrive with a single clean export. They have multiple partial sources of truth: chart of accounts, creditor/debtor masters, cost centres, BU codes, VAT codes, and often long booking histories with inconsistent descriptions. Your job is to work with each client only as much as needed, infer structure from messy data, and turn it into clear rules and reference data so our AI pre-accounting stays accurate.

You bridge real-world accounting messiness and how Cortena models reference data (masters in spreadsheets / connected accounting systems + guideline documents). You will work directly with our founding team so clients go live smoothly, outputs stay trustworthy, and the product improves from what you see on the ground.

This is not a ticket-chasing support role. You will have real ownership from day one.

What you will do

Client reference data & onboarding (core)

• Own “source of truth” discovery with minimal friction: figure out the smallest set of asks (files, exports, system access) to obtain chart of accounts, creditor/debtor lists, cost centres, BU/VAT context where relevant, and historical postings when masters alone are incomplete.

• Normalize inconsistent inputs: combine spreadsheets, CSVs, PDFs, and accounting exports; resolve naming chaos, duplicates, and missing codes; align creditor/debtor identifiers with booking behaviour where needed.

• Infer structure from booking history: mine long transaction lists to recover stable patterns (which accounts, suppliers, and descriptions recur), deduplicate noise, and use that to validate or complete chart-of-accounts and allocation logic.

• Capture how the business actually operates: identify the client’s main line(s) of business, typical spend, and recurring ambiguous line descriptions; turn that into practical matching rules (when the system must choose between accounts, cost centres, or BU codes).

• Translate into Cortena setup: ensure reference data and guidelines are reflected in our tenant configuration (connected systems, Google Drive reference sheets, and guideline sources the product uses for classification)—and flag gaps to the product team before they become client incidents.

AI Quality Assurance

• Review AI-processed invoices and transactions against the reference data and guidelines you helped define; catch systematic misclassifications, not one-off quirks.

• Flag edge cases and misclassifications, document patterns, and feed insights back to the team

• Document patterns (good and bad), suggest evaluation checks and prompt/flow improvements, and help keep quality measurable as we ship changes.

• Help develop and maintain evaluation frameworks to measure output quality over time

• Contribute to prompt testing and improvement as our AI workflows evolve

Client Communication

• Be a clear, structured point of contact for onboarding data questions - not every ad-hoc request, but the data and setup thread.

• Turn client reality into short, actionable notes for engineering (what was messy, how you resolved it, what the product should do better next time).

• Act as a first point of contact for onboarding questions and technical setup issues

• Translate client feedback into clear product and improvement notes for the team

• Keep onboarding documentation up to date and easy to follow

What we are looking for

Must-have

• Genuine interest in AI applied to real finance work — you use AI tools and understand limits (hallucinations, brittle rules) as well as strengths.

• Solid intuition for bookkeeping and SME finance: invoices, GL accounts, cost allocation, creditors/debtors, and how posting history relates to masters.

• Structured problem-solving: comfortable with large tables, reconciliation, and “good enough” triage when data is incomplete.

• Excellent communication: you can say what is wrong, why it matters, and what we should do - briefly.

• Detail-oriented — you notice when something is off and you follow it through

Nice to have

• Exposure to DATEV, Exact Online, Twinfield or similar; comfort with Excel/CSV and Google Sheets at volume.

• Experience turning ambiguous natural language (invoice lines, memo fields) into routing rules or guidelines.

• German language skills.

What you will get

• Direct exposure to founding-team decision making at an early-stage AI startup

• A front-row seat to how a real AI finance product is built and iterated

• Hands-on experience with production AI workflows and real client data

• Flexible hours — 20 hours per week or full-time, depending on your availability

• Based in Amsterdam, with occasional travel to Rotterdam

About Cortena

Cortena is an AI-native finance operations platform for SMEs in Europe. We automate the manual, repetitive work that finance teams deal with every day — invoice processing, pre-accounting, bank reconciliation, and more. We are backed by Builders Studio and based in Rotterdam, with our first paying clients already live in Germany.

We are a small, focused team. Every person we bring in shapes what we become.

To apply, reach out directly with a short note on why this role interests you and what you have been working on lately.