• 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.

• 5+ years of experience in solution architecture, with at least 3 years focused on designing and deploying generative AI, agentic AI, and ML solutions in enterprise environments.
• Hands-on experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn, Hugging Face, LangChain) and agentic AI platforms for LOB applications.
• Proven success in delivering AI/ML solutions for LOB use cases, such as automated customer service, content generation, predictive analytics.
• Expertise in generative AI techniques (e.g., LLMs, GANs, VAEs), agentic AI systems (e.g., autonomous agents, reinforcement learning), and ML algorithms (e.g., regression, clustering, decision trees).
• Proficiency in programming languages such as Python, R, or Java, with experience in AI/ML libraries and frameworks.
• Strong knowledge of data engineering, including ETL pipelines, data lakes, and big data tools (e.g., Spark, Hadoop) for LOB data needs.
• Experience with MLOps for deploying and managing generative AI, agentic AI, and ML models in production.
• Familiarity with cloud platforms (Azure preferred) and enterprise systems integration (e.g., APIs, microservices).
• Ability to align generative AI, agentic AI, and ML solutions with LOB objectives, such as increasing customer engagement, improving forecasting accuracy, or streamlining operations.
• Strategic thinking to identify high-value LOB use cases for AI/ML adoption.
• Proficiency in Agile and DevOps methodologies for rapid solution delivery.
• Deep understanding of enterprise architecture and AI/ML integration patterns for LOB systems.
• Commitment to ethical AI practices, particularly for generative AI outputs, agentic decision-making, and ML model fairness.
• Strong problem-solving and analytical skills tailored to LOB challenges.
• Excellent communication skills to articulate AI/ML benefits to non-technical LOB stakeholders.
• Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence. A master’s degree or PhD in AI, ML, or a related discipline is preferred.
• Dynamic personality, and you are confident in ambiguous situations.
• Fast learner and self-motivated to challenge status quo
• Flexible to work with team from time zones as global role
• Fluency in English (written and spoken; Minimum level: B2); 

• Secure job and salary – permanent contract in a technically exciting, stable, and sustainable industry and an attractive compensation package
• Social benefits and an attractive work calendar.
• Teamwork & safety – an open, transparent, and value-oriented culture
• Individualized training plan from your very first day.
• TK Elevator is a company with an open, transparent culture that focuses on the people who make it up. At TKE you will receive frequent feedback, continuous training and space to contribute your ideas.

At TKE we are committed to a corporate culture that values and is committed to diversity. We understand that different cultures, professional profiles, nationalities or gender enrich us and allow us to work together and achieve excellence. We are adhered to the world compact and the United Nations Declaration of Human Rights.

TK Elevator is a forward-thinking company where people can find the freedom to broaden their horizons and become part of a company that is diverse, exciting, innovative and, on top of all, stable. We have created a work environment that fosters respect, tolerance and diversity, where people can grow professionally and work in teams passionate about transforming the industry.

We are a company committed to people, society and the planet. Aligning our business success with attention to the needs of our social environment and the planet makes our brand even stronger and more sustainable. Our commitment goes from respecting our regulations and codes of conduct to our social policies in favour of integration, diversity and conciliation.