SAP GenAI & Agentic AI Engineer

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.
- Solid 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

📌 SAP GenAI & Agentic AI Engineer (Bengaluru)
🏢 PwC
📍 Bengaluru