AI Platform Engineer (m/f/d)

Own the target operating model for the CIT AI platform, including governed exploration, model access, deployment patterns, operational ownership and handover between teams and external partners. Define reusable platform patterns and standards for LLM APIs, RAG components, evaluation pipelines, AI gateway integration and business application integration. Set technical direction and priorities for MLOps Engineer(s), review key build decisions and ensure implementation choices remain aligned with platform standards. Own the transition path from sandbox or PoC environments into production-ready architectures, including support model, lifecycle ownership and operational readiness criteria. Define cost transparency and usage visibility for AI platform consumption, including token, cost and usage reporting patterns. Coordinate and steer nearshore, system integration and cloud implementation partners while retaining internal accountability for platform outcomes. Own platform decisions, security assumptions, interface documentation, architecture decisions and handover requirements at governance level. Act as the primary contact for architecture, security, governance, data engineering, cloud platform and application teams on AI platform matters. Report platform roadmap, risks, decisions, adoption progress and production-readiness status to CIO-level and senior stakeholders.