Development Architect (Artificial Intelligence), SAP Business Technology Platform
SAP Labs · Bangalore · 15+ yrs experience · Posted 2026-03-25
Tech stack: AWS, Azure, GCP, Java, Python
About the role
What You Build
Internal AI Frameworks: Design and build the SDKs and tools used by Application teams to develop, deploy, and scale AI agents.
Developer Efficiency: Lead the organization wide adoption of AI technologies to streamline coding, testing, and delivery workflows.
Agent Infrastructure: Architect core systems for agent orchestration, including memory management, tool-calling, and multi-agent coordination.
Observability & Maintenance: Implement robust monitoring for agent latency, cost, and accuracy to ensure production systems are stable and maintainable.
Responsibilities:
- What You Build
- Internal AI Frameworks: Design and build the SDKs and tools used by Application teams to develop, deploy, and scale AI agents.
- Developer Efficiency: Lead the organization wide adoption of AI technologies to streamline coding, testing, and delivery workflows.
- Agent Infrastructure: Architect core systems for agent orchestration, including memory management, tool-calling, and multi-agent coordination.
- Observability & Maintenance: Implement robust monitoring for agent latency, cost, and accuracy to ensure production systems are stable and maintainable.
Qualifications:
- Experience: 15+ years in cloud product development and AI/Machine Learning research or industry applications.
- Technical Mastery: Deep hands-on experience with LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangGraph, AutoGen).
- Cloud & Dev Stack: Expert proficiency in Python, Java and cloud infrastructure (AWS, Azure, or GCP).
- Efficiency Mindset: Strong focus on developer experience (DX) and creating reusable frameworks that simplify complex AI development.
- Strategic Leadership: Ability to translate business goals into technical architectures that engineering teams can easily adopt.
- Education: Bachelor's or Master’s in Computer Science, Engineering, or a related quantitative field.
- Where you Belong
- At SAP BTP Fabric, we aren’t just using AI—we are reimagining how software is built and how our business operates through it. We are seeking a visionary Architect to serve as the cornerstone of our AI transformation.
- Your mission is two-fold: lead the organization adoption of AI-driven development practices to 10x our engineering efficiency, and architect the core frameworks and tools that power our next generation of Autonomous Agents. You are a hands-on architect who bridges the gap between sophisticated cloud product development and cutting-edge Generative AI
Qualifications
- Experience: 15+ years in cloud product development and AI/Machine Learning research or industry applications.
- Technical Mastery: Deep hands-on experience with LLMs, prompt engineering, RAG, and agentic frameworks (e.g., LangGraph, AutoGen).
- Cloud & Dev Stack: Expert proficiency in Python, Java and cloud infrastructure (AWS, Azure, or GCP).
- Efficiency Mindset: Strong focus on developer experience (DX) and creating reusable frameworks that simplify complex AI development.
- Strategic Leadership: Ability to translate business goals into technical architectures that engineering teams can easily adopt.
- Education: Bachelor's or Master’s in Computer Science, Engineering, or a related quantitative field.
- Where you Belong
- At SAP BTP Fabric, we aren’t just using AI—we are reimagining how software is built and how our business operates through it.
- We are seeking a visionary Architect to serve as the cornerstone of our AI transformation.
- Your mission is two-fold: lead the organization adoption of AI-driven development practices to 10x our engineering efficiency, and architect the core frameworks and tools that power our next generation of Autonomous Agents.
- You are a hands-on architect who bridges the gap between sophisticated cloud product development and cutting-edge Generative AI
Responsibilities
- What You Build
- Internal AI Frameworks:
- Design and build the SDKs and tools used by Application teams to develop, deploy, and scale AI agents.
- Developer Efficiency: Lead the organization wide adoption of AI technologies to streamline coding, testing, and delivery workflows.
- Agent Infrastructure: Architect core systems for agent orchestration, including memory management, tool-calling, and multi-agent coordination.
- Observability & Maintenance: Implement robust monitoring for agent latency, cost, and accuracy to ensure production systems are stable and maintainable.