AI Administrator

Role : AI Administrator
Location : Houston, Texas
Long Term

Summary :

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