AI Platform Working Student

You will have direct ownership of tasks, contribute your own ideas, and actively shape how the platform evolves. This is not an observation role, you will work on the same codebase and infrastructure as the rest of the team.

What You Will Work On

• Deploy, configure, and maintain shared AI Hub instances across Azure and AWS
• Build and test platform tools, functions, and custom AI agents based on specifications
• Monitor platform health, uptime, logs, and configuration consistency across all deployed AI Hub instances
• Build health-check, alerting, and reporting scripts that track version parity, uptime, cloud usage, and deployment status
• Support containerized application deployment, environment configuration, secrets handling, and rollback processes
• Implement and validate integrations with infrastructure and enterprise services such as MCP servers, Git/Bitbucket, Microsoft Graph, and data providers
• Write deployment guides, runbooks, and onboarding documentation for new companies joining the platform
• Monitor core platform and dependency releases, then summarize operational impact, upgrade steps, and risks for the group

Requirements

What We Are Looking For

Required

• Currently enrolled in a Master's program in Computer Science, Data Science, AI/ML, Software Engineering, or related field
• Strong Python skills, comfortable writing scripts, calling APIs, and building small applications
• Comfortable with Bash/shell scripting and working in a Linux terminal
• Basic familiarity with cloud infrastructure and application deployment on Azure or AWS
• Practical experience using LLMs via API (OpenAI, Anthropic, or similar)
• Familiarity with Docker, REST APIs, Git, and deployment workflows
• Ability to read and work from technical documentation independently
• Strong written communication in English (fluent) and German (fluent)

Bonus

• Cloud platform certifications in Azure, AWS, or Google Cloud are a plus, especially when paired with hands-on deployment or operations experience
• Experience with cloud application platforms, LangChain, LlamaIndex, or agentic AI frameworks
• Infrastructure as Code awareness (Bicep, Terraform, CloudFormation)
• Familiarity with authentication concepts (OAuth, SSO, JWT)
• Experience with monitoring, logging, or cloud operations tools such as Azure Monitor or CloudWatch

Benefits

What You'll Get

• Work on infrastructure and tooling that directly shapes how 55+ software companies adopt AI, your output has immediate, visible impact across the group
• Become part of CHAPTERS Group, a German serial acquirer with 10x growth in the past five years and high ambitions for what comes next
• Full integration into the AI Core team, contributing alongside senior engineers from day one, with a direct line to the CTO office
• Hands-on experience building, deploying, and maintaining enterprise AI infrastructure across Azure and AWS in production
• Access to enterprise AI tooling: Claude Code, Azure OpenAI, and a modern multi-cloud AI platform stack
• Direct ownership of tasks with measurable impact, not support work or observation
• Active investment in your development: mentorship from the AI Core team, exposure to real architecture decisions, and access to relevant events and conferences

How to Apply

Send your CV along with a brief note on why this role interests you and what you would bring to the AI Core team. No formal cover letter required.

We are looking forward to your application!

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