AI-Native Engineer – Freelance

Oper Credits

AI-Native Engineer designing and building Python microservices for a fintech company. Collaborating to streamline bank integrations and enhance customer experiences.

Posted 5/13/2026contractAntwerp • 🇧🇪 BelgiumMid-LevelSeniorWebsite

Tech Stack

Tools & technologies

AWSCloudDockerPython

About the role

Key responsibilities & impact

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)
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

What you’ll need

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

Comp & perks

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

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonFastAPIPydanticRESTOpenAPIasync programmingAPI designDockerCI/CDobservability

Soft Skills

communicationself-managementcollaborationrisk managementproactive questioningdelivery rhythm managementdocumentationcode maintenance