AI Engineer (GraphRAG & Full-Stack)*

About BAWAG Group

BAWAG Group is the listed holding company of BAWAG, one of the largest banks in Austria with over 4 million customers. As a dynamic employer, we promote talent and drive technological innovation rapidly. Flat hierarchies, a flexible working environment, and equal opportunities for our employees are particularly important to us.

We are evolving from standard analytics to advanced AI engineering. We are looking for a builder who can navigate the full stack--from engineering backend APIs to designing the front-end interfaces that allow users to interact with complex AI models. You will play a key role in operationalizing our GraphRAG (Retrieval-Augmented Generation) systems, moving us from experimental scripts to robust, interactive applications.

Our Technology Stack

AI & Backend Engineering:

• Python (FastAPI): For building high-performance, asynchronous REST APIs to serve our models and graph data.
• GraphRAG & OpenAI: Leveraging generic Graph approaches and OpenAI models for advanced relationship mapping and knowledge retrieval.
• Graph Databases: (e.g., Neo4j, NetworkX, or similar) for storing and traversing complex knowledge structures.

Application Interface:

• Streamlit: For rapid prototyping and internal testing of algorithms.
• React: (Key Focus) For building the production interface that allows users to visualize, explore, and query our Knowledge Graphs intuitively.

Data Platform:

• Snowflake: For scalable analytics and structured data storage.

Orchestration & DevOps:

• Airflow: For orchestrating complex data and AI workflows.
• GitHub & Jenkins: For CI/CD, version control, and automated deployment.

What You'll Do

• Engineer AI Backends: Design and deploy scalable FastAPI endpoints that handle complex queries and serve data from our Knowledge Graphs to the frontend.
• Build Interactive Graph Interfaces: Take proven concepts from Streamlit and re-engineer them into responsive React applications. Your goal is to build UIs that make navigating complex graph data simple and actionable for business users.
• Optimize GraphRAG Pipelines: Refine our RAG strategies to ensure our AI retrieves the most relevant contexts from our graph structures.
• Productionize Prototypes: Bridge the gap between data science and software engineering by rewriting experimental Python code into production-grade, maintainable software.
• CI/CD & Deployment: Use Jenkins and GitHub to maintain a robust deployment pipeline for both the backend APIs and the frontend applications.

Who We Are Looking For

• Someone with a strong data/backend foundation (Python, API design) who is not afraid of the frontend.
• Experience or strong interest in React--specifically in how to visualize data (charts, graphs, networks).
• A "Product Engineering" mindset: You care about how the AI output is actually consumed by the user.

What we offer

• You will spend 50% of your working time in our modern and easily accessible office at Vienna Central Station.
• We support your personal development and career planning with an individual and attractive training program. Visit our BAWAG Academy and use our GoodHabitz elearning platform for both your professional and personal growth.
• In addition, we offer a range of interesting and valuable additional benefits

Salary

• For this position, the collective agreement stipulates a minimum annual gross salary of EUR 45.811,22 on a full-time basis. Depending on your experience and qualifications, we are willing to offer a higher salary.

Contact

• Your contact person: Jutta Durstberger +43 6648099822099

Our Values

• We value people.
• Would you like to work in a team where good cooperation and diversity are actively practiced? Then you've come to the right place. Equal opportunity is important to us - regardless of age, gender, sexual orientation, physical impairment, religion or origin.

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• Wir wertschätzen den Menschen. Chancengleichheit ist für uns wichtig - unabhängig vom Alter, Geschlecht, sexueller Orientierung, körperlicher Beeinträchtigung, Religion und Herkunft.

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