Requirements

Expected technologies

LiteLLM

mlflow

machine learning

Snowflake Data Cloud

knime

Our requirements

Requirements:

-Degree in Computer Science, Mathematics, Engineering, or a related field.

-Several years of professional experience in developing and architecting bespoke AI-based platforms.

-In-depth knowledge of Artificial Intelligence, machine learning, deep learning, and Natural Language Processing (NLP).

-Experience in selecting and integrating tools and frameworks such as LiteLLM, mlflow, snowflake, knime.

-Practical experience with cloud platforms (AWS, Google Cloud, Azure) and modern infrastructure technologies.

-Experience with agile development methods and working in cross-functional teams.

-Strong problem-solving skills and the ability to tackle complex technical challenges.

-Excellent communication skills in both German and English, both written and spoken.

Desirable:

-Experience in developing bespoke platforms and custom solutions for clients.

-Knowledge of Big Data technologies and Data Lakes.

-Understanding of DevOps practices and automated deployment pipelines.

-Experience with integrating real-time data streams and high-dynamics systems.

Your responsibilities

We are looking for an experienced AI Architect (m/f/d) who can design, implement, and continuously optimize a bespoke platform to meet our business needs. The AI Architect will play a key role in connecting visionary platform requirements with intelligent, scalable, and innovative technology.

Responsibilities:

-Design and implement a bespoke platform using advanced Artificial Intelligence and machine learning techniques.

-Lead and be responsible for the architecture of the entire platform, both from a technical and strategic perspective.

-Integrate various AI models, algorithms, and data sources into the platform to create intelligent and scalable solutions.

-Collaborate closely with cross-functional teams, including data scientists, software developers, and product managers, to successfully implement and continuously evolve the platform.

-Ensure platform stability and security, adhering to best practices for code quality and architecture.

-Conduct performance analysis and continuously optimize the platform to ensure scalability and efficiency.

-Create technical roadmaps and future visions for the platform’s development, including the integration of new AI technologies.