AI Platform Architect

Job summary

Join our innovative AI platform team, working on exciting projects. Enjoy a collaborative work environment with continual learning opportunities.

Tasks

Several years of experience in creating AI platforms; Master’s in relevant fields.
Strong technical skills in AI platform integration and architecture.
Proficient in Python, software engineering best practices, and communication.

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What to expect

Exciting and innovative AI platform projects for our clients: from creative workshops to proofs of concept to joint implementation of productive solutions
Conceptualisation and design of holistic AI platforms based on cloud or open-source components, from reference architecture to selection and integration of components
Definition of the technical target architecture and derivation of concrete, actionable work packages
Hands-on implementation: development of central platform components, code reviews and deployment across cloud and on-premises environments
Establishment of engineering standards and best practices for the platform, for example regarding evaluation, observability and deployment
Technical sparring partner for stakeholders: you translate requirements into viable architectural decisions and weigh technical options thoroughly
Close collaboration with our ML and AI engineers as well as software developers
Professional mentoring and coaching of junior colleagues
Technical lead in proposals including coordination of the involved experts
Continuous learning and ongoing professional development as well as insights into the various industries of our clients
Variety and exciting collaboration in internal project teams as well as on-site with our clients

What you bring

Several years of experience in the conception and implementation of AI platforms, ideally in productive use for clients or own products
A completed master’s degree in computer science, data science or a related field
Technical intuition for how holistic AI platforms can be composed from open-source components
Ability to clarify technical requirements with stakeholders and translate them into viable architectural decisions
Experience with agentic systems and AI workflows, RAG systems as well as the Model Context Protocol (MCP)
Careful approach to solution evaluation, familiar with Evaluation Driven Development (EDD) and AI evaluation and observability platforms (AEOPs)
Experience with model runtimes and LLM proxies or gateways
Experience with blob storage (S3) and relational databases (SQL)
Familiar with modern vector databases, as well as understanding of open-weight large language models, including multimodal models
Experience with deployments both in the cloud and on-premises, platform- and vendor-independent
Confident use of Python and software engineering best practices
Strong communication skills and enjoyment of collaboration with team and clients
Fluent German and English, both spoken and written

We are looking for you – become part of our team