SAP GenAI & Agentic AI Engineer_Manager
PwC
About the role
SAP GenAI & Agentic AI Engineer
Job Description
and Summary We are seeking a passionate and skilled SAP GenAI & Agentic AI Engineer with 9+ years of overall experience , including hands-on experience working with SAP environments and a minimum of 9 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
- 47 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
Eligibility & process
Who can apply
Experience: 9-13 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
19 resourcesStudy material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Explain the difference between Precision, Recall, and F1-Score. Answer
How does Gradient Descent work and what is the role of Learning Rate? Answer
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Behavioural & HR questions 3
Highlight PwC's market reputation, recent tech innovations, and how your skills in AWS directly solve their team's objectives.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Competitive Package (Best in Industry)
Bengaluru, India
Experience: 9-13 Yrs. Open to matching quโฆ
