Senior ABAP Developer

About Cirql One

We believe the real value of modern enterprises lies in their data.

Most large organizations already have the data they need. What they lack is a way to work with it at scale. Over time, meaning gets buried in legacy systems, configurations, customization, and undocumented logic. The data still runs the business, but it can’t easily be trusted, reused, or reasoned over consistently by modern software and AI.

SAP sits at the center of this problem. It runs the core business process of more than 90% of Fortune 500 companies. SAP has spent decades perfecting systems of record while AI is building systems of reasoning, and the real opportunity lies in connecting the two. SAP systems are deeply embedded, business‑critical, and designed to change slowly. They are complex systems, refined over decades to ensure precision and control. Yet while the data is reliable by design, its business meaning is often implicit and difficult for AI systems to interpret, which prevents AI from reasoning over it reliably, safely, and at scale.

At Cirql One, we’ve spent more than 30 years working inside these environments. We know why AI systems struggle to interpret enterprise data correctly, that many existing semantic layers stop at technical abstraction, and why business meaning must be made explicit to scale trust, reuse, and automate.

What We Do

Cirql One is a startup focused on building the missing link between ERP systems and AI : an SAP-native semantic intelligence layer that gives AI models and agents a shared, business-accurate understanding of enterprise data. Our vision is to be the new system-of-reason sitting above SAP - where intelligence, metrics, and AI automation are defined, governed, and executed.

The result is a stable foundation for AI, automation, and analytics that can evolve independently of the underlying systems.

Tasks

We are building a platform that manages immense complexity—ontologies, data pipelines, and AI reasoning. We are not looking for a traditional ABAP developer to build Z-reports or customize screens. We are looking for an expert who understands the heartbeat of SAP—ECC, S / 4HANA, and BW—and wants to unlock it for the modern AI world.

You will be the bridge between 30 years of ABAP logic, business semantics, and the future of agentic AI. You will write code that liberates business meaning and context from legacy configurations, allowing it to be trusted and reused by modern software.

This is a permanent, product-oriented role, not project-based consulting.

What You’ll Work On

• Modernize Data Access : Build clean, reliable extraction and integration logic that sits close to the data layer, prioritizing performance and stability.
• Reverse Engineer Meaning : Analyze complex, undocumented legacy logic to understand how business meaning is constructed inside SAP.
• Build Product, Not Projects : Unlike traditional consulting, you will build reusable core components of our platform that scale across different SAP environments.
• Collaborate with Cloud Architects : Work alongside the Platform and AI teams to ensure SAP data is exposed in a way that is consumable by the semantic layer.

Requirements

Benefits

If you want to apply deep SAP expertise in a modern product environment, we’d be glad to connect.

Apply directly or get in touch informally.

Cirql One is a startup focused on building the missing link between SAP ERP systems and

AI : an SAP-native semantic intelligence layer that gives AI models and agents a

shared, business-accurate understanding of enterprise data. Our vision is to be the

new system-of-reason sitting above SAP - where intelligence, metrics, and AI

automation are defined, governed, and executed.

The result is a stable foundation for AI, automation, and analytics that can evolve

independently of the underlying systems.

At Cirql One, we’ve spent more than 30 years working inside these environments. We

know why AI systems struggle to interpret enterprise data correctly, that many

existing semantic layers stop at technical abstraction, and why business meaning

must be made explicit to scale trust, reuse, and automation.