Platform Engineer

Who are we?

We are Exaloan, a FinTech based in Frankfurt, Germany, specializing in AI-based credit analytics. We provide professionally managed access to diversified portfolios of loans originated by FinTech and alternative lenders across Specialty Finance, SME and Consumer sectors. We operate a global digital lending marketplace at the intersection of asset management, software development, machine learning and generative AI, with the ambition to drive innovation in one of the fastest-growing sectors in finance. And we are unstoppable to reach our goals.

Location — please read before applying

This is a full-time, on-site role based in our office in the heart of Frankfurt. You must already live within commuting distance of Frankfurt, or be genuinely ready to relocate here before you start, and you must be authorized to work in Germany. We work together in the office; this is not a remote or majority-remote position. Please apply only if an on-site Frankfurt role is what you are looking for.

Who are we looking for?

We are looking for a Platform Engineer to roll out, operate, and scale the core infrastructure that powers our credit-analytics platform. The work is to run our data and scoring stack well, keep it healthy, and extend it as we onboard more origination platforms to our marketplace. This is a role for a disciplined operator who takes pride in a system that runs reliably and gets better without regressing: someone who improves what exists, respects the design and the guardrails around it, and makes each new platform onboarding smoother and more automated than the last.

You are a strong Python engineer, comfortable across data engineering and AWS, and fluent in the modern AI-assisted development workflow — one capable person, amplified by good tools, doing what used to take a small team.

Your role

• You will collaborate directly with founding partners who are seasoned experts across the domains integral to our work: capital markets, portfolio management, banking law, software engineering, machine learning and generative AI.
• From your first day, you will help roll out and operate our core platform — the standardized loan-data model, the scoring pipeline, and the MLOps serving layer — and own the onboarding of new lending platforms onto it.

Tech stack

Python, FastAPI, Celery, ArangoDB, AWS (ECS, Lambda, S3, CloudWatch), AWS CDK, Docker, pandas/NumPy, REST APIs, Bitbucket Pipelines. We build in an AI-assisted engineering environment and expect you to be fluent in it.

Key responsibilities

• Roll out and operate the core platform. Take our data-standardization, scoring, and model-serving components from integration into steady operation — deployed, monitored, and reliable — and keep them healthy as usage grows.
• Own partner onboarding end to end. Take a new lender’s export and carry it through ingestion, mapping to our standardized loan model, and into a live scoring instance — and improve that path with each platform you add.
• Maintain and extend without regressing. Improve the pipeline, the mapping layer, and the tooling around them while preserving the quality bar already built in. You work within — and help strengthen — the governance and technical guardrails (tests, coverage floors, a review gate, controlled change) that keep the platform from degrading as it scales.
• Turn manual steps into automated systems. Replace hand-run reporting and one-off scripts with tooling that makes onboarding and operation a repeatable process rather than a bespoke effort each time.
• Run the infrastructure it lives on — AWS provisioning, deployment, monitoring, logging, alerting, and cost control for data-processing and serving workloads.
• Own data quality: validation, reconciliation, and error handling throughout the pipeline, so that what reaches the scoring models and clients is trustworthy.
• Work closely with the data science and business development teams to ensure the platform meets modeling and reporting requirements.

Your profile

• At least 2 years of professional software-development experience in a relevant engineering role.
• Strong software-development experience in Python, particularly data processing, pipelines, and operating production systems.
• Experience running and maintaining data infrastructure in production — not only building it, but keeping it reliable, observable, and cost-effective over time.
• Excellent communication skills, bridging business and engineering teams
• Experience with ETL/ELT pipelines and integrating diverse, heterogeneous data sources and formats.
• Solid grasp of data modeling, schema design, and mapping — turning messy inputs into a canonical form.
• Hands-on with AWS (Lambda, ECS, S3, CloudWatch), containerization (Docker), and deployment automation; comfortable with CI/CD and Infrastructure as Code.
• A disciplined engineer who improves systems without eroding them — you respect an existing design and its guardrails, and you work inside a controlled, audited change process rather than around it.
• Fluent with AI-assisted development tools and eager to use them to cover more surface area. You can direct these tools and still own the correctness of what ships.
• You own outcomes end to end and can work independently on complex, ambiguous problems.
• Familiarity with ArangoDB or other NoSQL databases is advantageous.
• Experience with financial or lending data is a plus.
• Exceptional written and verbal communication skills in English.
• Based in the Frankfurt area or ready to relocate, and authorized to work in Germany (see Location, above).

What we offer

• A dynamic, fast-growing business — we are scaling up in one of the fastest-growing sectors in finance.
• Professional and experienced team.
• International environment and network.
• Central office in the heart of Frankfurt.
• Direct involvement in the entire trajectory of the firm.
• The possibility to grow and scale your role along the growth of Exaloan.
• 30 days of annual leave.
• A Deutschlandticket to make your commute easier.
• Access to Corporate Benefits (via Mitarbeiterangebote.de) for discounts on shopping, travel, and more.
• A learning and certification budget (e.g. AWS and other professional certifications).
• Modern equipment.

How to apply

Send your CV and a short note confirming that you are applying for a full-time, on-site role in Frankfurt. Our process is a first call (covering the role, location, and relocation), a technical interview, and a final conversation with the founding team. We share the salary range for this role on request, and discuss it during the first call.

Exaloan is an equal-opportunity employer. We welcome applications from all qualified candidates regardless of gender, age, ethnicity, religion, disability, sexual orientation, or background.

We hire for talent; hence you will be able to develop your role according to your personal goals and position yourself where you can make the biggest impact and contribution.

If you think you are a good fit for our team, send your application now!