Data Extraction Specialist – AI

Amsterdam - Rokin 111, 1012 KN

Live, first seen by us 52 days ago

Pay: Pay not listed
Work setting: Not stated
Employment: Permanent — employment source
Employment type in the employer’s posting: Permanent employee
From the employer’s posting

What you’ll work on

Full posting

Configure and tune DTA2 extraction across document types and fields
Design, build and deploy LLM-based extraction to replace existing rules
Build and maintain benchmarks showing where extraction improved or regressed
Implement engineering improvements across DocStreet, DTA2 and Orbis
Work with Product, Engineering, Lending Operations and clients

From the employer’s posting

Configure and tune DTA2 across different document types and fields

Design, build, evaluate and deploy LLM-based extraction within the engine.

Build and maintain the benchmarking loop that shows where extraction has improved, where it has regressed and why.

Identify and implement engineering improvements across DocStreet, DTA2 and Orbis.

Collaborate with internal stakeholders across Product, Engineering and Lending Operations, as well as directly with our clients.

What you’ll bring

All qualifications

Core experience

1–5 years of hands-on experience
Degree in Computer Science, Software Engineering, Data Engineering or comparable
Experience designing and iterating on prompts and LLM benchmarks

Qualification wording

1–5 years of hands-on experience

with a degree in Computer Science, Software Engineering, Data Engineering or a comparable field

You know how to design and iterate on prompts and how to build benchmarks that show whether a change actually helped.

Apply at Ohpen Services B.V.

Posting record

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Status in our records: Live
First seen by us: Sep 22, 202652 days ago
Recorded sightings: 34
Last seen by us: Nov 13, 2026

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How this job compares

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Day 52

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From 51 similar postings that came down. Coming down is not always a hire.

Ohpen Services B.V. is hiring

1 open job

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Java
AWS

Where the posting names them

NICE TO HAVE - Experience with Java and AWS, as our engine runs on them. - Dutch language skills, as most of the documents we extract are in Dutch.

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About the role

We file this job under AI Engineer, by the work the posting describes.

AI engineers build products on top of AI models that already exist, most often large language models: they connect a model to a company's data and tools and ship the assistants, agents and search features people use.

Postings ask for strong Python or TypeScript, experience with model APIs, retrieval and agent frameworks, and ways to test whether the model's answers are good enough.

An ML engineer trains and serves models; an AI engineer usually starts from a model someone else trained and builds the product around it, though titles often mix the two.

Job description

View original posting ↗

Description

Do you want to teach a bank’s document engine to read?

Every mortgage application comes with a stack of documents: payslips, employer statements, valuation reports, bank statements and IDs. Our extraction engine automatically turns these documents into structured data that can be used throughout the lending process.

Making that engine smarter is one of Ohpen’s key objectives for 2026, as we move from classical extraction rules towards AI/LLM-based extraction.

As a Data Extraction Specialist – AI, you’ll help drive that transition end-to-end. You’ll configure and optimise the engine, build the LLM-based extraction that replaces existing rules, benchmark the results to prove extraction rate.

Briefing

Ohpen launched the world’s first cloud-native core banking platform. Within our Lending Suite, several components work together to process every document that comes in with a mortgage application:

DocStreet is our document processing platform. It receives, classifies and routes incoming documents.
DTA2 is the data extraction engine within DocStreet. It reads each document and turns it into structured fields, such as income, employer and property value, which our clients’ lending processes rely on.
Orbis is the engine that executes automated validations on the extracted documents.

You’ll join our Transformation & Innovation team, working within a small and focused data extraction squad. A small team means high ownership and plenty of opportunity to make an impact.

WHAT YOU WILL DO

Improve extraction rates. Configure and tune DTA2 across different document types and fields, prioritising those that matter most to our clients.
Roll out AI/LLM-based extraction. Design, build, evaluate and deploy LLM-based extraction within the engine. This includes everything from prompt design and model selection to guardrails, evaluation sets and production rollout.
Prove that it works. Build and maintain the benchmarking loop that shows where extraction has improved, where it has regressed and why. No improvement ships without evidence.
Improve the engine itself. Identify and implement engineering improvements across DocStreet, DTA2 and Orbis.
Work closely with the people who use it. Collaborate with internal stakeholders across Product, Engineering and Lending Operations, as well as directly with our clients.

About You

You are analytically strong. You pick up new domains quickly and are comfortable being the person who figures out how things actually work.
You have a technical engineering background, with a degree in Computer Science, Software Engineering, Data Engineering or a comparable field, and 1–5 years of hands-on experience.
You are AI-native. LLMs are a normal part of how you work. You know how to design and iterate on prompts and how to build benchmarks that show whether a change actually helped.
You are a proactive self-starter. In a small team, there is no one to wait for. You spot what needs doing, propose it and take ownership of getting it done.
You are a strong communicator. You can explain technical trade-offs to clients, respectfully challenge colleagues when needed and keep stakeholders informed without being asked.

NICE TO HAVE

Experience with Java and AWS, as our engine runs on them.
Dutch language skills, as most of the documents we extract are in Dutch.
Familiarity with the Dutch mortgage market, ideally through previous experience working with Dutch mortgage products, processes or systems.

Why us?

Ownership of a strategic 2026 objective from day one, in a team small enough that your work is visible to both clients and leadership.
The opportunity to move a production system used by regulated lenders from rule-based to AI-based extraction.
A role at the intersection of engineering, AI and the Dutch mortgage domain.
Hybrid working from our office in the heart of Amsterdam.
Competitive compensation and benefits.

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