SAP GenAI & Agentic AI Engineer

SAP GenAI & Agentic AI Engineer

Job Description and Summary

We are seeking a passionate and skilled SAP GenAI & Agentic AI Engineer with 47 years of overall experience, including hands-on experience working with SAP environments and a minimum of 2 years in Generative AI (GenAI).

The ideal candidate will combine an understanding of SAP applications, data, integrations, and technical landscapes with strong hands-on expertise in Generative AI, Agentic AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Python, and modern AI engineering frameworks.

The AI Engineer will play a key role in designing, building, and deploying enterprise-grade AI solutions and accelerators that address SAP transformation and delivery use cases.

Responsibilities

• Design, develop, and deploy GenAI and Agentic AI solutions for SAP and enterprise use cases, with a strong focus on production readiness.
• Build and scale RAG-based solutions using SAP and enterprise data, documentation, technical artifacts, and knowledge repositories.
• Develop AI-powered accelerators supporting SAP use cases such as:
• SAP custom code analysis and modernization
• Functional and technical specification analysis
• SAP configuration and documentation analysis
• Code generation, review, and validation
• Test case generation and automation
• Data mapping and data validation
• SAP API and integration recommendations
• Impact analysis and knowledge assistants
• Integrate LLM solutions with SAP applications, APIs, services, and enterprise data sources.
• Build and integrate graph-based memory, tool-using agents, and context-aware AI solutions.
• Implement multi-agent orchestration and reasoning workflows using frameworks such as LangGraph, AutoGen, LangChain, or custom agent frameworks.
• Develop clean, efficient, reusable, and scalable Python-based AI services and APIs.
• Work with cloud-based LLM platforms such as Azure OpenAI, AWS Bedrock, or equivalent enterprise AI platforms.
• Collaborate with SAP functional, technical, data, integration, and business teams to translate business requirements into scalable AI-powered solutions.
• Implement evaluation frameworks to measure accuracy, relevance, groundedness, hallucination, performance, and reliability of AI solutions.
• Apply strong software engineering practices covering version control, automated testing, CI/CD, observability, security, and maintainability.
• Support deployment and operation of AI solutions in enterprise production environments.

Required Qualifications

• 4–7 years of overall experience in software engineering, SAP technology, AI/ML, or related technology areas.
• Minimum 2 years of hands-on experience building and deploying GenAI solutions.
• Prior experience working within SAP environments or on SAP transformation/implementation programs.
• Understanding of the SAP ecosystem, SAP business applications, data structures, APIs, integrations, and technical artifacts.
• Hands-on experience working with LLMs such as OpenAI GPT models, Claude, Gemini, or equivalent models.
• Strong hands-on knowledge of RAG architectures and Agentic AI frameworks such as LangGraph, LangChain, AutoGen, or equivalent frameworks.
• Strong proficiency in Python.
• Experience building APIs, microservices, containers, and cloud-native applications.
• Experience with vector databases, embeddings, semantic search, and enterprise knowledge retrieval.
• Experience with tool calling, agent orchestration, graph-based memory, or memory-augmented AI architectures.
• Understanding of prompt engineering, context management, grounding, and hallucination mitigation.
• Solid understanding of software engineering practices including Git/version control, testing, CI/CD, and code quality.
• Ability to work effectively with SAP technical and functional teams and translate SAP requirements into AI engineering solutions.

Preferred Qualifications

• Hands-on experience with one or more SAP technologies such as ABAP, CDS, RAP, SAP BTP, SAP Integration Suite, SAP APIs/OData, or SAP HANA.
• Experience building AI solutions or accelerators specifically for SAP use cases.
• Understanding of SAP S/4HANA transformation and Clean Core principles.
• Experience integrating AI solutions with SAP BTP or SAP S/4HANA.
• Experience with Azure OpenAI, AWS Bedrock, or other enterprise LLM platforms.
• Experience with tool-using agents, multi-agent systems, memory-augmented architectures, or cognitive architectures.
• Experience with LLM evaluation, optimization, observability, and production monitoring.
• Prior contributions to open-source GenAI or agent frameworks are advantageous.
• Experience deploying and maintaining AI systems at enterprise scale.

Mandatory Skill Sets

• Generative AI (GenAI)
• Agentic AI
• Python
• RAG and LLM application development
• SAP experience/background