SAP Enterprise AI Consultant

Overview

As an SAP Enterprise AI Analyst, you will help build and deploy the next-generation SAP AI platform within Accenture’s SAP Business Group. You’ll work under senior engineers on live client engagements, configuring BTP services, managing ingestion pipelines, and validating citations. The role develops deep expertise in a focused area of the platform while coordinating with cross-functional teams. This is a hands-on, pace-driven opportunity to shape enterprise AI delivery for SAP environments.

Pay / Benefits

• up to 25 days’ vacation
• private medical insurance
• 3 extra days leave for charitable work
• onsite client work flexibility

Responsibilities

• Support build and deployment of the SAP AI platform on client projects
• Configure and monitor SAP BTP services (HANA Cloud, Object Store, Job Scheduler, CAP runtime) under guidance
• Develop and maintain ingestion pipelines and extraction validation routines
• Schedule jobs and perform health checks and smoke tests to standard
• Spot-check citations against source documents and escalate defects
• Document ingestion scope, data owners and inventory details with cross-team alignment
• Provide project updates and escalate issues to senior engineers and delivery lead

Key requirements

• Working knowledge of SAP BTP services (HANA Cloud, Object Store, Job Scheduler, CAP runtime)
• Understanding of RAG pipelines and vector/graph stores
• Scripting capability in Python or Node.js for ingestion tooling
• Awareness of data masking and scrubbing requirements
• Experience with citation validation and quality checks
• Familiarity with enterprise security basics (egress rules, RBAC, service keys)
• Ability to gather source inventory, confirm data owners, document ingestion scope
• Structured, repeatable approach to technical tasks like ingestion runs and health checks
• Clear written and verbal communication for status updates and escalation

• Strong communication
• Attention to detail
• Collaborative teamwork
• SAP BTP services: HANA Cloud, Object Store, Job Scheduler, CAP runtime
• RAG pipelines: document chunking, embedding, tagging, vector/graph store
• Python or Node.js scripting for ingestion tooling

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