Enterprise AI Platform & Agent Infrastructure for FUNKE Mediengruppe

Python Google ADK Model Context Protocol (MCP) LiteLLM Cloud Run Terraform Open WebUI Multi-Agent Systems

Working closely with Chief AI Officer Dr. Paul Elvers and Executive Board Member Stephan Thurm, I co-architected and built the enterprise AI and agent infrastructure for FUNKE Mediengruppe, one of Germany's largest media organizations. Operating across editorial, business, and operational divisions, the platform serves 5,000+ active users with a 92% monthly retention rate, generating an estimated €2M+ in annual productivity value (featured in an official Google Cloud Customer Success Story).


To turn scattered AI tools into a governed, company-wide capability, we built the platform around an architectural paradigm called "One platform, three doors":

  1. The Workbench (Open WebUI): An accessible interface where newsrooms, business teams, HR, and legal can switch between models and create tailored internal assistants.
  2. The Gateway (FUNKE AI API via LiteLLM): A central routing and policy layer that "right-sizes" spend—directing high-volume queries to fast Gemini Flash models and complex tasks to frontier reasoning models—processing over 40 billion tokens with granular budget and SSO controls.
  3. The Agent Layer (Google ADK & Gemini Engine): A managed, serverless runtime powering autonomous agents, shared memory, and sandboxed execution environments.

My work focused on hands-on development across the agent framework, tools, sandboxes, and enterprise rollouts:

  • Multi-Agent Orchestration & Core Agents: Engineered production agent templates (chat & batch) with automated CI/CD and Terraform IaC modules. Built the multi-agent Business Development Agent Team (supervisor agent, specialized subagents, shared state synchronization, and custom Open WebUI rendering functions), alongside production agents like the Synthetic / Deepfake Image Detection Agent (Cloud Run GPU inference with computer vision benchmarks, Sightengine, and Copyleaks integrations) and the Deep Research Agent (a 5-stage pipeline cutting hours of editorial research to under 10 minutes).
  • Model Context Protocol (MCP) Ecosystem: Designed, deployed, and secured a registry of 20+ enterprise MCP servers packaged in Artifact Registry. Connectors include internal documentation (MPP360), Germany's national news agency (dpa), regional editorial databots, statistical data (Destatis), Periscope/Poliscope, and Slack integration via FastMCP, with full OAuth 2.1 / OIDC token delegation and secret management.
  • Secure Execution Sandboxes & Isolation: Architected and built an MCP server abstraction layer on top of Google Cloud's sandbox solution (Agent Engine runtime). Implemented user management with a custom OAuth delegation flow so individual employees could provision and interact with secure, isolated sandboxes with shell access and computer use capabilities restricted exclusively to them.
  • Model Governance & Intelligent Right-Sizing: Configured centralized LiteLLM gateway governance routing over 40 billion tokens across Gemini Flash, Claude Opus 4.7/5.5, and Sonnet 4.6. Implemented granular SSO user budgets, token rate limiting, and automated credential rotation.
  • Enterprise Client Rollouts & Enablement: Led the corporate rollout of modern AI desktop and CLI clients across business units and executive leadership—integrating Claude Desktop, Claude Code, OpenCode, and OpenWork into existing IT systems. Tailored client-specific configurations, permissions, and security guardrails, and built automated build-time bi-lingual documentation (DE/EN) for the internal FUNKE AI Developer Portal.
Featured Case Study

Build only what lasts: FUNKE's AI platform on Google Cloud

Google Cloud published an in-depth customer story detailing how FUNKE transformed scattered tools into an enterprise capability on Google Cloud infrastructure—routing 40B+ tokens, scaling to 5,000+ monthly active users (92% retention), and generating over €2M in annual productivity value.

Architecture Breakdown

FUNKE AI — Das Gateway bleibt

Chief AI Officer Dr. Paul Elvers shared an architectural perspective on why owning the central AI gateway creates compounding value while individual models become commodities—highlighting how centralized routing, caching, and MCP tooling scale across the company. Browse the 9-slide carousel below.

"We engaged Julius to develop custom AI prototypes for our business, and he exceeded our expectations. His deep knowledge spans both the technical infrastructure side and software development aspects of AI implementation. I would highly recommend him to anyone looking for an experienced AI freelancer who can bridge the gap between technical complexity and real-world application."

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