About the job
CognitX AI GmbH is building a privacy-first AI advisor for data analytics and process automation. We let people ask complex questions about their data in natural language and get trustworthy answers visualizations and automated actions. Our architecture connects directly to enterprise sources leverages a knowledge graph for context and executes analyses through a secure compute layer. On-prem and cloud deployments are first-class.
The Role
As a Working Student in AI/LLM Engineering youll help design build and evaluate Agentic AI systems that turn questions into reliable analytics and automated workflows. Youll work across model prompting/tool-use data access and evaluation collaborating closely with our senior AI experts on real enterprise use cases.
Tasks
What youll do:
- Build and improve agentic workflows (tool/function calling planning self-checks) for analytics summaries and visualizations task automation.
- Implement adapters/tools to connect LLMs with internal and external services.
- Contribute to our FastAPI backend (clean interfaces validation with Pydantic tests).
- Develop evaluation metrics to measure accuracy latency and cost.
- Optimize prompts retrieval/contexting and execution strategies for privacy reliability and performance.
- Ship in containers (Docker) and collaborate on deploys (Kubernetes) CI and observability.
- Document decisions and share learnings with the team.
Requirements
What you bring:
- Experience with LLMs/AI agents (function/tool calling RAG MCP or agent frameworks) and Machine Learning fundamentals.
- Strong Python skills for production code and data work (typing tests packaging).
- Familiarity with APIs and microservices (FastAPI preferred) Git and containerized dev (Docker).
- Solid problem-solving clear communication and a proactive ownership mindset.
- Currently enrolled in Computer Science Data Science AI or a related field (eligible to work as a Werkstudent:in).
Nice to have:
- Retrieval/RAG stacks (embeddings chunking evaluators) Redis PostgreSQL.
- Kubernetes GitLab CI observability (logs/metrics/traces).
- React/TypeScript for light UI tooling.
- Interest in EU privacy/GDPR and safety-by-design for enterprise AI.
- Exposure to self-hosted/open models (e.g. Llama Mistral etc) and model serving.
- Knowledge-graph concepts; graph queries.
Benefits
Why CognitX
- Work on meaningful privacy-first AI with real enterprise pilots.
- Learn fast with tight mentorship from a team of Senior AI Experts.
- Flexible hours remote-friendly and impact from day one.
- Competitive Werkstudent compensation.
About the jobCognitX AI GmbH is building a privacy-first AI advisor for data analytics and process automation. We let people ask complex questions about their data in natural language and get trustworthy answers visualizations and automated actions. Our architecture connects directly to enterprise s...
About the job
CognitX AI GmbH is building a privacy-first AI advisor for data analytics and process automation. We let people ask complex questions about their data in natural language and get trustworthy answers visualizations and automated actions. Our architecture connects directly to enterprise sources leverages a knowledge graph for context and executes analyses through a secure compute layer. On-prem and cloud deployments are first-class.
The Role
As a Working Student in AI/LLM Engineering youll help design build and evaluate Agentic AI systems that turn questions into reliable analytics and automated workflows. Youll work across model prompting/tool-use data access and evaluation collaborating closely with our senior AI experts on real enterprise use cases.
Tasks
What youll do:
- Build and improve agentic workflows (tool/function calling planning self-checks) for analytics summaries and visualizations task automation.
- Implement adapters/tools to connect LLMs with internal and external services.
- Contribute to our FastAPI backend (clean interfaces validation with Pydantic tests).
- Develop evaluation metrics to measure accuracy latency and cost.
- Optimize prompts retrieval/contexting and execution strategies for privacy reliability and performance.
- Ship in containers (Docker) and collaborate on deploys (Kubernetes) CI and observability.
- Document decisions and share learnings with the team.
Requirements
What you bring:
- Experience with LLMs/AI agents (function/tool calling RAG MCP or agent frameworks) and Machine Learning fundamentals.
- Strong Python skills for production code and data work (typing tests packaging).
- Familiarity with APIs and microservices (FastAPI preferred) Git and containerized dev (Docker).
- Solid problem-solving clear communication and a proactive ownership mindset.
- Currently enrolled in Computer Science Data Science AI or a related field (eligible to work as a Werkstudent:in).
Nice to have:
- Retrieval/RAG stacks (embeddings chunking evaluators) Redis PostgreSQL.
- Kubernetes GitLab CI observability (logs/metrics/traces).
- React/TypeScript for light UI tooling.
- Interest in EU privacy/GDPR and safety-by-design for enterprise AI.
- Exposure to self-hosted/open models (e.g. Llama Mistral etc) and model serving.
- Knowledge-graph concepts; graph queries.
Benefits
Why CognitX
- Work on meaningful privacy-first AI with real enterprise pilots.
- Learn fast with tight mentorship from a team of Senior AI Experts.
- Flexible hours remote-friendly and impact from day one.
- Competitive Werkstudent compensation.
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