This role involves developing custom software solutions, focusing on designing, coding, and enhancing components across various systems. The emphasis is on leveraging modern frameworks and agile methodologies to deliver scalable, high-performance solutions tailored to specific business requirements.

Key responsibilities include building AI-native, HANA-optimized SAP applications and extensions. This is achieved by combining deep ABAP on HANA engineering expertise with agentic AI patterns like LLMs, tools, retrieval, and evaluation. The position prioritizes delivering production-grade solutions that utilize HANA pushdown principles, modern ABAP, and governed AI capabilities.

We are not focused on training or fine-tuning foundation models from scratch. Instead, this role actively builds and owns AI behaviors, including grounding, evaluation, guardrails, and observability, as integral parts of SAP solution delivery.

Design and implement ABAP solutions meticulously optimized for SAP HANA, adhering to pushdown principles to minimize data movement and maximize in-database processing. Develop efficient data models and access patterns using CDS views, associations, annotations, and authorization concepts. Implement performance-critical logic with AMDP/SQLScript where applicable, ensuring careful governance and testing. Create modular, testable, and maintainable ABAP code that aligns with clean architecture practices and enterprise SDLC. Build stable services and APIs using modern paradigms like OData, ensuring versioning and contract-first behavior. Consistently apply secure coding standards and authorization checks across data and service layers. Model enterprise business entities using CDS semantics for both transactional and analytical consumption. Design reusable data artifacts supporting downstream consumers, including UI, integrations, analytics, and AI retrieval layers. Ensure lineage-friendly structures and consistent business definitions. Build AI-enabled SAP experiences integrating ABAP services with LLM capabilities, including tool calling orchestration, retrieval-grounded outputs, and deterministic fallbacks. Implement prompts, tool schemas, and context assembly strategies to reduce hallucinations and enforce enterprise safety boundaries. Develop automated tests for ABAP services and data artifacts to enforce regression coverage. Establish evaluation harnesses for AI behaviors using golden datasets and scenario-based tests. Introduce guardrails for AI outputs, including context filtering, redaction rules, action confirmations, and audit logs. Instrument services with logs, metrics, and traces suitable for production support. Design robust error handling for enterprise flows with retries, idempotency, and safe failure modes. Support incident response with runbooks and continuous hardening of solutions based on observed failure patterns. Integrate ABAP on HANA services with SAP and non-SAP ecosystems. Collaborate with cross-functional teams to ensure end-to-end solution correctness and performance. Rapidly prototype, demonstrate frequently, and evolve prototypes into scalable production systems with security and compliance integrated.

Possess strong hands-on expertise in ABAP Development on HANA, including performance tuning, pushdown optimization, and efficient SQL access patterns. Demonstrate proficiency with CDS views and modern data modeling practices, covering associations, annotations, and authorization concepts. Showcase 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. Have AI native build capability, including LLM integration, retrieval grounding, tool orchestration, evaluation loops, and establishing safety boundaries. Experience with OData/service design patterns, API lifecycle management, and contract-first development is strongly 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 a plus. Understanding of SAP security/authorizations and compliance requirements for sensitive enterprise data is preferred.