AI Solutions Manager (d/f/m) TK Elevator Innovation & Operations GmbH

Responsibilities

• Architect end-to-end AI and ML solutions , emphasizing generative AI (e.g., text, image, or code generation), agentic AI systems (e.g., autonomous agents for decision‑making), and ML models (e.g., predictive analytics, classification) to address LOB use cases like personalized marketing, customer support automation, financial forecasting, and operational efficiency.
• Provide technical expertise to development teams , ensuring generative AI, agentic AI, and ML solutions are scalable, secure, and integrated with enterprise systems.
• Partner with LOB leaders, data scientists, and IT teams to identify high-impact use cases , define requirements, and translate business needs into robust AI/ML architectures.
• Evaluate and recommend AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain, AutoGen)
• Design data pipelines to support generative AI, agentic AI, and ML models, ensuring high-quality data for training, fine‑tuning, and inference in LOB contexts, such as customer data for personalization or transactional data for predictive analytics.
• Integrate AI/ML solutions with enterprise systems (e.g., Salesforce, SAP, or marketing platforms) to enable seamless LOB adoption and interoperability.
• Optimize generative AI models, agentic systems, and ML algorithms for performance, cost‑efficiency, and accuracy in production, addressing LOB‑specific KPIs like prediction accuracy, response time, or customer satisfaction.
• Establish governance frameworks for AI/ML solutions , ensuring compliance with regulations (e.g., GDPR, CCPA) and ethical standards, particularly for sensitive LOB applications like customer data handling or financial modeling.
• Stay abreast of advancements in generative AI (e.g., multimodal models), agentic AI (e.g., multi‑agent systems), and ML techniques (e.g., ensemble methods, reinforcement learning), proposing innovative solutions to enhance LOB outcomes, such as automated content creation, intelligent process orchestration, or predictive maintenance.
• Mentor data scientists, developers, and architects in best practices for designing and deploying generative AI, agentic AI, and ML solutions for LOB use cases.