Design, build, and deploy AI-powered applications, agents, and intelligent automations that solve real business problems across multiple domains.
Apply Model Context Protocol (MCP) and related standards to connect large language models and AI agents securely to enterprise systems and data sources.
Use n8n (or similar workflow automation tooling) to orchestrate AI-driven workflows, combining LLM reasoning with deterministic business logic.
Identify and lead AI-enablement opportunities across platforms such as SAP SuccessFactors, ServiceNow, and Global Identity and Access Management (GIAM), working with the respective platform teams.
Own end-to-end delivery of AI initiatives — from prototyping and experimentation through to production deployment, monitoring, and continuous improvement.
Define technical approach and architecture for AI initiatives, evaluating build-vs-buy options, model choice, and integration patterns.
Ensure AI solutions are secure, explainable, and compliant, partnering with Security, Enterprise Architecture, and Compliance teams on responsible-AI practices.
Mentor and guide junior developers on AI engineering practices, prompt design, and workflow orchestration.
Act as a technical point of contact for AI-related initiatives, engaging stakeholders across business and IT to translate needs into practical AI solutions.
Stay current with the fast-moving AI ecosystem (models, frameworks, agent protocols) and champion responsible adoption across the organization.