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Accenture India Private Limited is seeking a Custom Software Engineer for a project role in Bengaluru. The role focuses on designing and building ABAP Cloud applications with LLM-driven intelligence embedded in SAP processes.
You will implement AI-enabled SAP extensions, develop robust RESTful interfaces, and integrate with enterprise APIs, ensuring scalable, secure solutions. 15 years of education and strong software engineering fundamentals are required.
Custom Software Engineer Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs. Must have skills : SAP ABAP Cloud Good to have skills : NA Minimum 15 year(s) of experience is required Educational Qualification : 15 years full time education Summary AI Powered Tech Talent. Build AI native, cloud ready SAP solutions on ABAP Cloud by combining deep ABAP and SAP platform expertise with agentic AI architectures, LLM tooling, and rapid experimentation. The role focuses on designing, implementing, and scaling intelligent SAP applications that integrate ABAP Cloud with LLMs, retrieval pipelines, APIs, and enterprise systems—moving from automation to autonomy. This role actively builds AI systems, not just consumes AI tools.
AI Native SAP Application Build Design and build ABAP Cloud applications that embed LLM driven intelligence into SAP business processes. Implement AI enabled SAP extensions using RESTful ABAP Programming Model (RAP), event driven patterns, and cloud native architectures. Develop clean, testable ABAP code that integrates seamlessly with AI services and enterprise APIs.
Agentic & LLM Integration Implement agentic workflows: tools, planners, memory, orchestration, and evaluation loops integrated with SAP processes. Integrate LLMs, embeddings, and retrieval pipelines (RAG) with ABAP Cloud services for contextual, grounded responses. Design prompt templates, grounding strategies, fallback logic, and safety boundaries suitable for enterprise SAP use cases.
Data, Retrieval & Context Build and integrate retrieval pipelines using SAP and non SAP data sources (business objects, CDS views, documents, events). Implement chunking, indexing, embeddings, and context assembly to support production grade RAG scenarios. Ensure factuality, traceability, and explainability in AI driven SAP workflows.
Quality, Safety & Reliability Implement evaluation frameworks (offline and online) for AI behaviors integrated with SAP processes. Design guardrails for authorization, data privacy, action boundaries, and error handling. Build observability into AI enabled SAP applications (telemetry, logging, failure analysis).
Rapid Experimentation & Scale Out Prototype quickly, demo frequently, and iterate based on business feedback. Move AI prototypes into enterprise grade SAP production systems with performance, security, and compliance in mind. Continuously refine AI behavior, prompts, and orchestration strategies.
A 15 years full time education is required.