Senior SAP AI Architect

Senior SAP AI Architect

Location: Anywhere in India

Job Description:

Role Overview

We are seeking a visionary and hands-on SAP AI Architect to lead the strategy, design, and implementation of

next-generation Enterprise AI solutions. In this role, you will be the technical anchor for our AI transformation,

focusing heavily on building intelligent agents and digital assistants.

The ideal candidate possesses a unique blend of deep enterprise architecture knowledge and extensive

hands-on experience deploying AI via both low-code frameworks (e.g., Joule Studio) and pro-code engineering

(e.g., custom LLM orchestration and frameworks) within the SAP BTP ecosystem.

Key Responsibilities

AI Architecture & Agent Orchestration

• End-to-End Agentic AI: Design and deliver architectures that integrate seamlessly with SAP S/4HANA,

SAP SuccessFactors, and non-SAP systems.

• Multi-Agent Systems: Architect workflows using foundational/advanced communication methodologies,

ensuring interoperability via the Agent-to-Agent (A2A) protocol.

• Tool Integration: Standardize landscape interaction by implementing the Model Context Protocol (MCP) for

secure internal and external tool interactions.

• AI Governance: Govern the lifecycle using the SAP LeanIX AI Agent Hub to discover, optimize, and manage

enterprise-wide AI capabilities.

Low-Code Assistant Delivery

• Digital Assistants: Build, configure, and seamlessly register corporate digital assistants via Joule Studio in

SAP Build.

• Visual Workflows: Utilize drag-and-drop interfaces to design complex business workflows, managed

runtimes, and automated tasks without traditional code.

Pro-Code AI Engineering

• Custom AI Engines: Develop high-performance AI engines using the SAP Cloud SDK for AI via Python,

Java, or TypeScript.

• Advanced Orchestration: Orchestrate multi-agent behaviors, memory systems, and custom tool-calling

using frameworks like LangGraph or CrewAI.

• Cloud Deployments: Deploy containerized custom AI microservices efficiently on cloud runtimes like Kyma

or SAP BTP Cloud Foundry.

Data & Core Infrastructure Integration

• Model Orchestration: Leverage SAP AI Core and the Generative AI Hub to securely orchestrate,

benchmark, and deploy large language models (LLMs).

• Enterprise RAG: Implement advanced retrieval mechanisms using Retrieval-Augmented Generation (RAG),

capitalizing on the SAP HANA Cloud Vector Engine and Knowledge Graph Engines.

Required Technical Skills & Qualifications

Core SAP AI Stack

• SAP Platform: Hands-on mastery of SAP BTP (Cloud Foundry / Kyma), CAP Framework, and SAP

Integration Suite.

• AI Control Plane: In-depth working experience with SAP AI Core, Generative AI Hub, AI Launchpad, and

Joule.

• Low-Code Toolkit: Complete proficiency in Joule Studio and the SAP Build suite.

Pro-Code & Engineering Frameworks

• Languages: Strong, production-grade programming skills in Python (required) along with Node.js/TypeScript

or Java.

• Orchestration Libraries: Deep practical knowledge of GenAI orchestration frameworks (e.g., LangChain,

LangGraph, CrewAI, LlamaIndex).

• Data Tiering: Expert knowledge of Vector Databases, semantic search, prompt engineering, and graph

technologies.

Integration & DevOps

• APIs & Protocols: Mastery of OData, REST, Event-Driven Architectures, A2A protocols, and MCP (Model

Context Protocol).

• Cloud Native: Familiarity with Kubernetes, Docker containerization, and enterprise CI/CD pipelines.

Experience & Education Requirements

• Overall IT Experience: Minimum of 8+ years in enterprise software architecture and engineering.

• AI/SAP Specific Experience: At least 3+ years of dedicated, hands-on experience designing and deploying

Generative AI or Agentic AI systems, specifically within an SAP context.

• Education: Bachelor's or Master's degree in Computer Science, Data Science, or a heavily quantitative field.

• Certifications (Preferred): SAP BTP certifications, SAP AI specialized credentials, or formal cloud platform

architect certifications.