Freelancer Curriculum & Content Lead – AI Architect Course (m,f,d)

Das ist der Job

Role Overview We are seeking a Subject Matter Expert (SME) with deep experience in AI Architecture.

Darum lohnt es sich

Build content to ensure industry relevance and future‑readiness to reflect modern architectural patterns. Collaboration closely with product and teaching teams in a flexible, remote‑friendly environment on course content.

What We Offer We provide an international, passionate, and fun working environment, a platform to grow as part of a dedicated team, and an opportunity to join one of the fastest‑growing companies in tech‑education.

The SME will own the framework and content of the course — designing and creating learning outcomes, modules, case studies, exercises, assessments, and handouts.

The SME must be strategic, hands‑on, and accountable for real impact to ensure the course content is created for a next‑generation professional course that equips learners to design, deploy, and scale enterprise‑grade AI infrastructure. The SME will be creating course content that goes well beyond tool usage or theory.

The content will enable the learners how to: Design and build production‑ready enterprise AI/ML architectures and cloud platform blueprints. Orchestrate LLM pipelines, multi‑agent workflows, and next‑generation connectivity protocols across scalable data systems.

Integrate vector databases, MLOps platforms, and developer frameworks with real cloud infrastructure. Evaluate, monitor, and enforce governance, cost‑control, and compliance on deployed models.

The SME will create course content such that graduate students can step into technical leadership roles, confidently balancing system performance, computing costs (FinOps), data privacy, and operational scalability in production.

Core Tasks Define a compelling, differentiated AI Architecture course curriculum outline that positions this course as a market leader. Develop advanced, practical content for this course – building all core learning materials so that learners walk away with applied skills, not just conceptual understanding.

Build high‑impact assessments and practicals for this course – creating real business scenarios and case challenges, hands‑on labs, peer reviews, project rubrics, portfolio deliverables, etc., so that the learners produce tangible artifacts.

Required Worked as AI Architect, AI Solutions Architect, Enterprise AI Architect, Cloud AI Architect, or a similar role in the industry. Proven hands‑on experience designing and scaling production AI/ML architectures using cloud platforms such as Azure AI and AWS Bedrock alongside Docker and Kubernetes.

Strong engineering experience with orchestration frameworks (LangGraph, CrewAI), vector databases, MLOps tools (Kubeflow, MLflow), and the Model Context Protocol (MCP). Practical knowledge of model cost‑estimation (Token‑burn analysis), scalability planning, C‑level reporting, and European compliance frameworks including GDPR and the EU AI Act.

Prior experience in curriculum design, instructional design, course development, or professional training is highly preferred. We value diversity and are committed to integration and diversity.

All applicants should be valued equally – regardless of gender and gender identity, nationality, ethnic origin, religion or belief, disability, age, sexual orientation, and identity. #J-18808-Ljbffr