AI Solutions Architect

Our client is expanding its AI capabilities and is looking for an experienced AI Solutions Architect to take ownership of the company’s AI landscape. This is a strategic and hands-on position focused on designing enterprise-grade AI platforms, shaping technical direction, and ensuring AI initiatives deliver measurable business value.

The successful candidate will work closely with engineering teams, business leaders, and data specialists to build scalable, secure, and production-ready AI ecosystems., * Develop the long-term AI architecture roadmap and align it with business and technology strategies.

• Design robust AI and machine learning platforms that are scalable, reliable, and secure.
• Assess, recommend, and implement appropriate AI technologies, cloud services, and development frameworks.
• Partner with engineering, data, and product teams to deliver high-quality AI solutions that satisfy technical, operational, and regulatory requirements.
• Bridge the gap between research and real-world implementation by transforming innovative AI concepts into production systems.
• Define architecture standards, governance policies, and best practices for responsible AI adoption.
• Drive technical decision-making across AI initiatives and provide architectural guidance to multidisciplinary teams.
• Establish processes for model deployment, monitoring, performance optimization, and continuous improvement throughout the AI lifecycle.
• Stay informed about emerging AI technologies and identify opportunities to enhance existing solutions.

• Candidates must already reside in Berlin or be prepared to relocate.
• Applicants must be eligible to work in the EU, as visa sponsorship is not available.
• Professional proficiency in English is essential., * Master’s degree or PhD in Computer Science, Artificial Intelligence, Data Science, or another relevant discipline.
• Demonstrated experience delivering enterprise AI solutions, including a minimum of three years in an architectural or technical leadership capacity.
• Strong technical background in machine learning and deep learning, with expertise in areas such as NLP, computer vision, or similar AI technologies.
• Practical experience with leading cloud environments including AWS, Microsoft Azure, or Google Cloud Platform.
• Hands-on knowledge of modern AI frameworks and libraries, including TensorFlow, PyTorch, and Hugging Face.
• Solid understanding of distributed systems, API-driven architectures, microservices, and large-scale data processing.
• Experience implementing MLOps practices, including CI/CD for ML, automated deployment, model versioning, and production monitoring.
• Familiarity with AI governance, explainability, responsible AI principles, and compliance considerations.
• Strong analytical mindset with excellent communication and stakeholder management skills.
• Experience working with business intelligence, advanced analytics, or AI-powered operational platforms is advantageous.
• Previous leadership or mentoring experience within cross-functional engineering teams.
• Exposure to Edge AI, telecommunications, or high-performance computing environments is considered a plus.
• Excellent spoken and written English.