(Junior) AI Solution Architect (f/m/d)

Transform your world with us! 

Fujitsu is a global partner for digital transformation and has set itself the goal of making the world more sustainable and promoting trust in society through innovation. With around 124,000 employees, Fujitsu supports its customers in over 100 countries in solving some of humanity's greatest challenges. The service and solution portfolio for sustainable transformation is based on five key technologies: Computing, Networks, AI, Data & Security and Converging Technologies.  

We offer an appreciative and flexible working environment that promotes work-life balance and actively supports individual career development. Diversity, equal opportunities and inclusion are core values of our corporate culture. Together, we have the future in mind - and for this we need people with vision.  

Apply now as (Junior) AI Solution Architect(f/m/d) for one of our locations, throughout Germany

Legal Entity: Fujitsu Technology Solutions GmbH 

We would like to fill the position as soon as possible. 

We are seeking a highly skilled and (Junior) AI Solution Architect to design, develop, and deploy innovative on-premise AI solutions for our clients, with a particular focus on Fujitsu's Private GPT and other similar offerings. The ideal candidate will possess a deep understanding of AI/ML technologies, on-premise infrastructure, and software architecture principles. This role requires strong communication and collaboration skills to work effectively with cross-functional teams, including data scientists, engineers, and clients. The AI Solution Architect will play a critical role in shaping our on-premise AI strategy and delivering high-impact solutions that address our clients' business challenges while prioritizing data security and sovereignty. 

What do we offer you?   

• Solution Design & Architecture: Design and develop robust, scalable, and maintainable on-premise AI solutions, considering factors such as performance, security, data sovereignty, and cost-effectiveness. This includes defining system architecture, data pipelines, model deployment strategies (focused on on-premise infrastructure), and comprehensive monitoring frameworks. 
• Hardware & Infrastructure Selection: Evaluate and recommend appropriate hardware components, including GPUs, TPUs, high-performance storage solutions (e.g., NVMe, parallel file systems), and networking infrastructure (high-speed interconnect technologies) to optimize AI model performance and scalability within the on-premise data center. 
• Technology Selection & Evaluation: Evaluate and select appropriate AI/ML technologies and tools for on-premise deployment, considering factors like security, scalability, maintainability, and hardware compatibility. Expertise in optimizing solutions for on-premise environments is crucial. 
• Data Strategy & Management: Define data strategies, including data acquisition, preprocessing, cleaning, and transformation, ensuring data security and compliance throughout the entire lifecycle, within the constraints of on-premise infrastructure. 
• Model Development & Deployment: Collaborate with data scientists to integrate AI models into on-premise production systems, utilizing appropriate deployment strategies (e.g., containerization within the on-premise environment). 
• API Design & Integration: Design and implement RESTful APIs and integrate AI solutions with existing on-premise systems and applications. 
• System Monitoring & Optimization: Implement robust monitoring and logging systems to track AI model performance, identify potential issues, and optimize system performance within the on-premise environment. 
• Documentation & Communication: Create comprehensive technical documentation, including system architecture diagrams, data flow charts, and API specifications. Effectively communicate technical concepts to both technical and non-technical audiences. 
• Client Interaction: Collaborate with clients to understand their business needs, gather requirements, and present technical solutions, emphasizing the benefits of on-premise AI deployments. 
• Team Collaboration: Work effectively with cross-functional teams, including data scientists, engineers, and product managers, to deliver high-quality on-premise AI solutions. 
• Staying Current: Stay abreast of the latest advancements in AI/ML technologies and best practices, with a focus on on-premise deployment strategies and security considerations. 

What qualifications should you have?   

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. 
• 2+ years of experience as an AI Solution Architect or similar role, with a demonstrable focus on on-premise deployments. 
• Strong understanding of AI/ML algorithms, techniques, and best practices. 
• Experience with on-premise infrastructure and deployment strategies. Experience with containerization technologies (Docker, Kubernetes) in on-premise environments is essential. 
• Proficiency in programming languages. 
• Excellent communication, presentation, and interpersonal skills. 
• Ability to work independently and as part of a team. 
• Experience with Agile development methodologies. 

Bonus Points: 

• Experience with specific AI/ML frameworks (TensorFlow, PyTorch, scikit-learn) deployed on-premise. 
• Experience with MLOps tools and practices adapted for on-premise environments. 
• Experience with specific industry verticals (e.g., finance, healthcare, manufacturing) and their on-premise IT infrastructure. 
• Experience with Fujitsu Private GPT or similar on-premise AI solutions. 

Interested? 

The job sounds exciting, but you're not sure if you meet all the requirements? Don't hesitate to apply. In addition to your skills, your personality and your potential count for us. We look forward to receiving your application, stating the earliest possible starting date and salary expectations. http://www.fujitsu.com/de/