01Overview
Strong proficiency in Python.
Experience with JavaScript/TypeScript, Node.js, or Java.
Hands-on experience with LLMs (GPT, Claude, Gemini, Llama, etc.).
Experience in Agentic AI, RAG, Prompt Engineering, and Function Calling.
Knowledge of LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
Experience with Vector Databases such as Pinecone, Chroma, Weaviate, Qdrant, or SAP HANA Cloud.
Exposure to Cloud & DevOps tools including Azure/AWS/GCP, Docker, Kubernetes, and CI/CD.
Experience in REST APIs, Microservices, Enterprise Integrations, and preferably SAP BTP Integration Suite.
Hands-on experience in AI Agent Development using MCP Servers, A2A Protocols, and SAP Integration Suite or similar platforms.
Good understanding of Responsible AI, AI Governance, and AI Security & Compliance.
Develop AI-powered applications, AI agents, and copilots across SAP and other enterprise platforms.
Design and implement RAG architectures, vector search capabilities, and AI orchestration frameworks.
Build scalable backend services, APIs, and microservices using modern software development practices.
Integrate AI solutions with SAP systems, ERP data sources, and enterprise business applications.
Ensure security, scalability, observability, performance, and production readiness of AI solutions.
Collaborate with business stakeholders, product teams, and architects to deliver end-to-end AI use cases.
Implement responsible AI practices, governance controls, and compliance standards.
Candidates with experience in SAP BTP, SAP AI Core, AI Launchpad, SAP Business AI/Joule Studio, SAP Build Code, CAP (Cloud Application Programming Model), SAP Integration Suite, and SAP HANA Cloud will be preferred. However, these skills are not mandatory.
Ideal candidates will come from backgrounds such as AI Engineer, GenAI Engineer, Agentic AI Developer, Full Stack AI Engineer, or SAP BTP AI Developer, with a strong passion for building enterprise-grade AI solutions and intelligent automation capabilities. .
