AI-Native Engineer (Freelance)

Oper, a European Fintech company, is a leader in cloud-based digital mortgage software. We provide personalized journeys for borrowers and lenders. Oper's technology streamlines the mortgage application process, eliminates paperwork, and increases transparency. Currently collaborating with 16 leading financial institutions across 6 European countries, our digital solutions result in a +27% increase in digital customer conversion, +81% faster mortgage decisions, and a 90% first-time-right.

Oper's AI Analyst, Herman, is a mortgage underwriting agent that automates document validation, data extraction, fact-checking, and credit policy application to deliver fully explainable, decision-ready loan recommendations in minutes instead of hours.

A passionate and engaging team of over 40 stellar Fintech operators works vigorously to transform European mortgages by enhancing efficiency and alleviating borrower anxiety. Backed by Bessemer Venture Partners and Motive Ventures, our platform has raised EUR 14 million, placing Oper at the forefront of revolutionizing mortgages in Europe. Oper is based in Antwerp, Belgium.

We are looking for an AI-Native Engineer to join us on a freelance, project-based engagement of around 6 months. The mission is to design and build a production-grade integration layer between Oper's product and a major European customer's banking systems, in the form of a Python microservice.

This is a hands-on engineering role for someone who is all-in on AI as the way they build software. We are not hiring for output measured in lines of code; we are hiring for someone who can use modern AI tooling to deliver something close to 5x the value a traditional engineer would, on a real, well-scoped problem.

If the engagement goes well and similar projects come up, we are very open to extending or starting new ones together.

Tasks

Build the integration layer

Design and build a Python microservice that acts as the integration layer between Oper's product and the customer's banking systems

Define clean API contracts (REST, OpenAPI) on both sides of the integration

Implement reliable request handling, retries, idempotency, and error semantics across system boundaries

Translate between Oper's domain model and the customer's data formats and protocols

Treat the integration as a real product: versioned, documented, and easy to evolve

Ship a production-ready service

Build the service with FastAPI, async patterns, and strong typing

Set up observability end to end: structured logging, tracing, metrics, alerts

Handle authentication, secrets, and sensitive data correctly from day one

Containerize and deploy via our existing CI/CD setup

Write meaningful tests at the right level (unit, integration, contract)

Deliver in an AI-native way

Use modern AI coding tooling (Cursor, Claude Code, Copilot, or your own setup) as a core part of how you build, not as an afterthought

Apply AI to the parts of the work where it actually compounds: scaffolding, adapters from spec, generating tests, reviewing diffs, writing documentation

Be honest about where AI helps and where it does not, and design your workflow accordingly

Aim for a delivery cadence and output level that a non-AI-native engineer simply cannot match

Collaborate and communicate

Own the delivery rhythm: weekly demos, written updates, clear progress signals

Ask the right clarifying questions early and proactively flag risk

Work closely with the Oper engineering, product, and customer-facing teams

Leave behind code, documentation, and runbooks that the internal team can confidently maintain after the engagement

Requirements

We are looking for a senior, pragmatic engineer who has shipped real integration work and is genuinely excited about AI-augmented delivery.

5+ years of backend engineering experience, ideally with a strong focus on integrations between systems

Deep, hands-on Python experience: idiomatic Python, async, typing, packaging, testing

Strong production experience with FastAPI (and Pydantic) on real services, not toy projects

Solid grasp of REST and API design: OpenAPI, versioning, error handling, pagination, contracts

Experience with async patterns, queues, and event-driven design: retries, idempotency, dead letters, backpressure

Comfortable with cloud and deployment: Docker, CI/CD, infrastructure as code, deploying real services to AWS or equivalent

Strong observability and security instincts: structured logging, tracing, metrics, secrets management, careful handling of sensitive customer data

Genuinely AI-native: you can name the tools, the workflows, and the concrete recent projects where AI gave you real leverage

Excellent communication and self-management: you set the rhythm, you flag risk early, you do not need to be chased

Bonus: experience with regulated industries, banking, or other environments with strong compliance and security expectations

Benefits

Freelance, project-based engagement of around 6 months

Target start date: June 2026

Ideally based in Belgium, fully remote within the EU is fine, working in CET hours

Possibility to extend or take on follow-up projects if the collaboration goes well

Day rate to be discussed based on experience

All equipment and access needed to do your best work