Student trainee for AI development
—
Your role in the team • Further development of our AI/LLM landscape in a hybrid environment • Development and maintenance of AI workflows and KOSTAL internal assistants; creation, testing, and versioning of system prompts and prompt templates (including guardrails). • Implementation of data and inference pipelines (ETL, embeddings, vector storage/caching); integration via REST/GraphQL and microservices. • Connection and secure integration of KOSTAL systems for the development and orchestration of AI agents and assistants • Monitoring, telemetry, and automated evaluation (quality, costs, performance), testing, and troubleshooting in operations (DevOps/MLOps). Technologies and skills • Helm • Flask • GraphQL • Kubernetes • Git • Docker • Python • FastAPI • RESTful API • GitLab Our expectations: Qualifications • Good programming skills, ideally in Python (FastAPI/Flask). • Fundamentals in Containers and Orchestration (Docker, Kubernetes on-premise and in the cloud, e.g., AKS), Helm; Version control and CI/CD (Git/GitLab). • API integration and interface competence desirable • Good English skills - Good German skills welcome Experience • Initial practical experience with LLMs/GenAI (Prompting, RAG, Evaluation) as well as with REST APIs. • Experience with data processing and databases Education • Ongoing studies in Computer Science, Data Science, Electrical Engineering, Mathematics, or a related field.
| Skill | Source | Confidence |
|---|---|---|
| MLOps | llm_hard |
100%
|
| Python | llm_hard |
100%
|
| Docker | llm_hard |
100%
|
| Kubernetes | llm_hard |
100%
|
| Large Language Models (LLMs) | llm_hard |
100%
|
| ETL Pipelines | llm_hard |
100%
|
| Data Pipelines | llm_hard |
100%
|
| Prompt Engineering | llm_hard |
100%
|
| RAG (Retrieval-Augmented Generation) | llm_hard |
100%
|
| Git | llm_hard |
100%
|
| Model Deployment | llm_hard |
80%
|
| Skill | Source | Confidence |
|---|---|---|
| Digital Literacy | llm_soft |
100%
|
| Written Communication | llm_soft |
80%
|
| Problem-Solving | llm_soft |
80%
|
| Analytical Thinking | llm_soft |
80%
|
| Learning Agility | llm_soft |
80%
|
| Query | Country | Status | Response ms | Created |
|---|---|---|---|---|
| Student trainee for AI development | extracted | 5253 | 2026-03-22 03:06 | |
| Student trainee for AI development | classified | 454 | 2026-03-21 21:12 | |
| junior AI developer in Germany | de | processed | 7932 | 2026-03-21 17:08 |
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"job_description": "Your role in the team\n• Further development of our AI/LLM landscape in a hybrid environment\n• Development and maintenance of AI workflows and KOSTAL internal assistants; creation, testing, and versioning of system prompts and prompt templates (including guardrails).\n• Implementation of data and inference pipelines (ETL, embeddings, vector storage/caching); integration via REST/GraphQL and microservices.\n• Connection and secure integration of KOSTAL systems for the development and orchestration of AI agents and assistants\n• Monitoring, telemetry, and automated evaluation (quality, costs, performance), testing, and troubleshooting in operations (DevOps/MLOps).\n\nTechnologies and skills\n• Helm\n• Flask\n• GraphQL\n• Kubernetes\n• Git\n• Docker\n• Python\n• FastAPI\n• RESTful API\n• GitLab\n\nOur expectations:\n\nQualifications\n• Good programming skills, ideally in Python (FastAPI/Flask).\n• Fundamentals in Containers and Orchestration (Docker, Kubernetes on-premise and in the cloud, e.g., AKS), Helm; Version control and CI/CD (Git/GitLab).\n• API integration and interface competence desirable\n• Good English skills - Good German skills welcome\n\nExperience\n• Initial practical experience with LLMs/GenAI (Prompting, RAG, Evaluation) as well as with REST APIs.\n• Experience with data processing and databases\n\nEducation\n• Ongoing studies in Computer Science, Data Science, Electrical Engineering, Mathematics, or a related field.",
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