Principal Generative AI Engineer

Role Overview

• Responsible for designing, building and continuously evolving prototypes, use cases and technical concepts around Generative AI, modern data platforms and cloud solutions
• Provide end-to-end advisory to our clients on shaping future-proof Data & AI strategies — from target architecture and technical enablement to stable production operations
• Design, implement and enhance scalable data architectures and cloud-based data warehouse solutions (e.g., on Azure or AWS)
• Ensure high quality standards in projects, particularly in prompt design, model evaluation, data science and validation of AI outputs
• Act as technical lead or active contributor in projects focused on AI architectures, end-to-end workflows and the operation of foundation models (on-premise or in the cloud)
• Develop and deliver internal training formats and actively transfer knowledge to strengthen our expertise in Generative AI and modern data platforms
• Continuously explore, test and evaluate new tools, APIs and frameworks (e.g., OpenAI, Hugging Face, Aleph Alpha) in areas such as NLP, Conversational AI, diffusion models or transformer architectures
• Maintain a presence in the professional community by attending conferences, meetups and events and by delivering talks, demos or technical publications
• Provide technical support to Sales and Marketing, for example through architecture concepts, technical arguments or participation in client presentations
• Actively participate in the continued development of our Swiss location in close collaboration with management and sales

Requirements

• Completed university degree in computer science, data science, mathematics or a comparable technical/scientific discipline
• Several years of professional experience (at least 5 years) implementing data, analytics or AI solutions, ideally in a project or consulting environment
• Excellent communication skills in German, Swiss German and English
• Practical experience with generative AI approaches and a solid understanding of foundation models (e.g., GPT, LLaMA, Claude), including fine-tuning strategies
• Strong Python skills (object-oriented), ideally complemented by experience with Spark and relevant open-source frameworks (e.g., Hugging Face, LangChain)
• Experience working with AI and LLM APIs (e.g., OpenAI, Aleph Alpha, Hugging Face) as well as foundational knowledge in NLP, probabilistic models, Conversational AI and diffusion techniques
• Deep understanding of modern cloud infrastructures (Azure or AWS) and knowledge of deployment, CI/CD and MLOps processes
• Advantageous: experience operating open-source models on-premise, on specialized accelerators or in the context of physical computing
• Strong communication skills and enjoyment of collaborating with clients, teams and the tech community
• Independent, solution-oriented working style with a willingness to take responsibility and travel for projects

Tech Stack

• AWS
• Azure
• Cloud
• Python
• Spark

Benefits

• Work-life balance
• Trust-based working hours with flexible scheduling, hybrid work model, workation — option to work from EU countries
• Unique team atmosphere, flat hierarchies up to our CEO Alex and an open feedback culture, annual team workshops at our Data.Castle in the Zillertal, lived Data.Musketeer principle — “one for all, all for one!”, our [at] Buddy program to improve networking, regular professional and social events
• Intensive onboarding & induction process, personal development plan and individual training opportunities, a broad range of workshops and courses within the Data.Academy delivered by our experienced Data.Musketeers and external providers, career paths in leadership, project management and technical expertise
• Numerous corporate benefits & employee offers (e.g., for events and travel), starter credit in our internal merchandise shop, competitive salary with variable components
• Mental health & wellbeing support as well as coaching and meditation via nilo.health, regular employee surveys