Student Assistant (SHK)

Company Description

The University of Siegen is seeking a motivated Student Assistant to support the development of a GenAI-based chatbot system. The position is intended for students with strong technical skills in backend development, PostgreSQL, Python, FastAPI, and workflow integration.

The role is particularly suitable for students in Computer Science, Data Science, Information Systems, Software Engineering, or a related field who are interested in applied generative AI, database-backed chatbot systems, and research-oriented software development.

Language: English

Role Description

The student assistant will contribute to the further development of an existing chatbot system that combines generative AI with structured technical data. A central part of the work will be to extend the current database setup to PostgreSQL and connect structured database information to the chatbot workflow.

The position focuses on backend, database, and workflow-related tasks. The student will work with PostgreSQL, SQL data modeling, Python, FastAPI, Docker Compose, Git, n8n workflows, and GenAI-based chatbot components.

In addition to technical implementation, the role includes supporting literature review, GenAI experiments, chatbot testing, and documentation.

Qualifications

The student assistant will support the design and implementation of a PostgreSQL-based database structure for the chatbot system. This includes modeling structured technical data, preparing database tables and relationships, and supporting the extention from the current database setup to PostgreSQL.

The role also includes connecting PostgreSQL data sources to chatbot workflows, particularly through backend services and n8n-based workflow components. The student will help integrate structured SQL-based information with existing RAG or PGVector-based chatbot results, so that the chatbot can make better use of both structured and unstructured knowledge sources.

Further responsibilities include supporting prompt and agent design, testing chatbot responses against expected database facts, identifying failure cases, documenting implementation steps, and contributing to literature review and GenAI-related experimental work.

Required Skills

Applicants should have good knowledge of the following areas:

PostgreSQL and SQL

Applicants should be comfortable working with PostgreSQL databases, including creating databases, schemas, tables, indexes, views, and read-only users. They should understand common PostgreSQL data types such as integer, text, timestamp, and jsonb, and be able to write SQL queries for structured data.

A solid understanding of SQL data modeling is required. This includes defining primary keys, foreign keys, relationships, and useful indexes, as well as translating table descriptions into practical database structures.

Python and FastAPI

Strong Python skills are required. Applicants should be able to write clean and maintainable backend code and should have knowledge of FastAPI for backend development and API integration.

Python may also be used for automation tasks, test scripts, dummy data generation, and supporting chatbot-related backend functionality.

Docker Compose and Development Workflows

Applicants should be familiar with Docker Compose and container-based development environments. Relevant tasks may include adding PostgreSQL services, managing ports and volumes, mounting seed files, configuring environment variables, and connecting services across containers.

Git is required for version control and collaborative development. Applicants should be comfortable working with repositories, branches, commits, and project documentation.

n8n Workflow Development

Knowledge of n8n or willingness to work with workflow-based automation tools is important. The student will support the creation and modification of workflows that connect PostgreSQL queries with chatbot components.

This may include configuring PostgreSQL credentials, adding database query nodes, passing query results into chatbot workflows, and debugging workflow execution and data mapping.

Generative AI and Chatbot Systems

Applicants should have a strong interest in GenAI-based systems and chatbot development. Relevant knowledge includes prompt engineering, LLM-based chatbot behavior, RAG-based systems, PGVector, and the integration of structured database results into LLM workflows.

The student should understand the importance of reducing hallucinations, handling missing database information correctly, and evaluating chatbot answers against expected factual results.

Database Access and Security

Applicants should have an understanding of safe database access practices. This includes working with read-only users, avoiding unnecessary exposure of sensitive data, and using dummy or anonymized data for development and testing.

Knowledge of PostgreSQL access configuration

Nice-to-Have Skills

The following skills are not mandatory, but would be considered an advantage:

• Experience with database administration or inspection tools such as pgAdmin or DBeaver
• Basic understanding of networking concepts relevant to database access, including host addresses, ports, firewall settings, VPN connections, and Docker-to-host communication
• Experience with Docker-based development environments and containerized database services
• Familiarity with chatbot evaluation, including the design of test questions and comparison of generated answers against expected results
• Basic knowledge of data privacy, anonymization, and secure handling of test or production data
• Experience with RAG-based systems, PGVector, or other approaches for combining structured and unstructured information in LLM applications
• Previous experience working with technical, scientific, or industrial data

Applicant Profile

We are looking for a reliable and technically skilled student who can work independently and communicate clearly. The ideal candidate has a structured working style, good documentation habits, a research-oriented mindset, and the ability to analyze technical problems and propose practical solutions.

Applicants should be enrolled at a university and should not be in their first semester. Students from Computer Science, Data Science, Information Systems, Software Engineering, or related fields are preferred.

Application Documents

Applicants should send the following documents:

• CV
• Current transcript of records
• Short statement of motivation or relevant experience
• Optional: GitHub profile, portfolio, or examples of previous technical work