This role involves developing custom software solutions, focusing on designing, coding, and enhancing components across various systems and applications.

Leveraging modern frameworks and agile methodologies, you will deliver scalable, high-performing solutions precisely tailored to unique business requirements.

The core of this position is to build AI-native, HANA-optimized SAP applications and extensions. This requires a deep understanding of ABAP on HANA engineering combined with agentic AI patterns, including LLMs, tools, retrieval, and evaluation.

You will focus on delivering production-grade solutions that are cloud-ready and exhibit high performance. This is achieved through HANA pushdown principles, modern ABAP development, and governed AI capabilities that can reason, retrieve context, and assist or act within enterprise SAP workflows, all without needing to train foundational models from scratch.

Design and develop ABAP solutions optimized for SAP HANA, emphasizing pushdown principles to minimize data movement and maximize in-database processing.

Build efficient data models and access patterns using CDS views, associations, annotations, and authorization concepts.

Implement performance-critical logic with AMDP/SQLScript, ensuring careful governance and thorough testing.

Develop modular, testable, and maintainable ABAP code following clean architecture practices and enterprise SDLC standards.

Build robust services and APIs using modern paradigms like OData, ensuring stability, versioning, and contract-first behavior.

Apply secure coding standards and consistently implement authorization checks across data and service layers.

Model enterprise business entities using CDS semantics to support both transactional and analytical consumption.

Design reusable data artifacts that benefit downstream consumers, including UI, integrations, analytics, and AI retrieval layers.

Ensure lineage-friendly structures and consistent business definitions to reduce ambiguity across systems.

Build AI-enabled SAP experiences that integrate ABAP services with LLM capabilities, encompassing tool calling orchestration, retrieval-grounded outputs, and deterministic fallbacks.

Implement prompts, tool schemas, and context assembly strategies that minimize hallucinations and enforce enterprise safety boundaries.

Develop automated tests for ABAP services and data artifacts to ensure regression coverage for performance and correctness.

Establish evaluation harnesses for AI behaviors, including offline golden datasets, scenario-based tests, and online monitoring.

Introduce guardrails for AI outputs, such as authorization-aware context filtering, redaction rules, action confirmations, and audit logs.

Instrument services and critical logic with logs, metrics, and traces for effective production support and root-cause analysis.

Design robust error handling for enterprise flows, incorporating retries, idempotency, correlation IDs, and safe failure modes.

Support incident response with runbooks and structured diagnostics, continuously hardening solutions based on observed failure patterns.

Integrate ABAP on HANA services with SAP and non-SAP ecosystems using event-driven patterns, API gateways, and enterprise integration layers.

Collaborate with UX, integration, data, and platform teams to ensure end-to-end solution correctness and performance.

Prototype rapidly, demonstrate solutions frequently, and evolve prototypes into scalable production systems with security and compliance integrated from the outset.

Demonstrate strong hands-on expertise in ABAP Development on HANA, including performance tuning, pushdown techniques, and efficient SQL access patterns.

Possess proficiency with CDS views and modern data modeling practices, covering associations, annotations, and authorization concepts.

Have experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown.

Exhibit solid software engineering discipline, encompassing clean design principles, a testing mindset, CI/CD orientation, and a focus on production readiness.

Showcase AI-native build capabilities, including LLM integration, retrieval grounding, tool orchestration, evaluation loops, and implementing safety boundaries.

Experience with OData/service design patterns, API lifecycle management, and contract-first development is highly beneficial.

Familiarity with integrating SAP backends with cloud runtimes and enterprise integration platforms is advantageous.

Knowledge of performance benchmarking, load testing, and query-plan driven tuning practices is strongly recommended.

Understanding of SAP security, authorizations, and compliance requirements for sensitive enterprise data is a plus.

Requires 15 years of full-time education.