- Employment
- Employee
About the role
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, 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, you’ll help design, build, and evaluate Agentic AI systems that turn questions into reliable analytics and automated workflows. You’ll work across model prompting/tool-use, data access, and evaluation, collaborating closely with our senior AI experts on real enterprise use cases.
Tasks
**What you’ll 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 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, 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, you’ll help design, build, and evaluate Agentic AI systems that turn questions into reliable analytics and automated workflows. You’ll work across model prompting/tool-use, data access, and evaluation, collaborating closely with our senior AI experts on real enterprise use cases.
Tasks
**What you’ll 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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