AI Administrator
- Tanisha Systems Inc.
3 Days Ago
NA
C2C
Houston-TX
7-10 Years
Required Skills: SAP Joule, BTP, AI/copilot platforms
Job Description
Embeds directly with the functional to rapidly build and integrate Joule capabilities. Owns the technical build for POCs and production deployments, connecting Joule to surrounding systems and iterating quickly based on direct business feedback.
Key Responsibilities
- Design and implement integrations between Joule, SAP S/4 , Datasphere, Integration Suite, and third-party systems such as Microsoft Copilot
- Troubleshoot integration and performance issues across the Joule technical stack
- Troubleshoot performance issues with AI modules and apply capacity management best practices to optimize Joule and AI Core workloads
- Identify AI solutions which can leverage SAP AI Core, SAP BTP, Joule, AI agents, RAG, Knowledge Graphs, vector databases, MCP, tool calling, evaluation frameworks, and AI observability – All teams
- Define reusable engineering patterns, reference architectures, golden paths, CI/CD standards, and deployment governance for enterprise AI delivery
- Define requirements for MCP Servers, and supporting platform services
- Leverage SAP AI Hub and SAP AI Gateway to evaluate and integrate foundation models and external AI services
- Document technical architecture and hand off supportable solutions to IT
- Keep IT informed of technical decisions, dependencies, and risks
- Leverage SAP AI Hub and SAP AI Gateway to evaluate and integrate foundation models and external AI services.
- Determine integration requirements between SAP applications, MCP services, business data sources, and external AI providers.
- Experience integrating Joule with other chat bots like Copilot, etc
- Work closely with SAP developers, BTP administrators, integration specialists, AI engineers, architects, and functional teams to deliver solutions.
Qualifications
- Experience with SAP Joule, BTP, or similar AI/copilot platforms
- Familiarity with SAP Datasphere and enterprise data integration patterns
- Deep understanding of LLM application architecture, including agentic AI, RAG/GraphRAG, Knowledge Graphs, vector databases, MCP, tool calling, evaluation frameworks, and AI observability
- Strong software engineering foundation, including Python, modern enterprise application architecture, Kubernetes, Docker, CI/CD, DevSecOps, hyperscaler platforms, and distributed systems
- Experience with SAP BTP and MCP Server concepts and architectures
- Comfortable working in ambiguous, fast-moving environments typical of forward-deployed roles
- Strong communication skills to work directly with non-technical business stakeholders
- Experience with Microsoft Copilot or similar enterprise AI integrations is a plus
- Experience with SAP document grounding and how it can be leveraged for various AI scenarios, and familiarity with SAP Business Data Cloud (BDC) AI use case scenarios
- Broad, adaptable skillset spanning software engineering, data engineering, and customer engagement, with comfort working across varied business domains and engaging both technical teams and executive stakeholders
