• Developing and enhancing conversational chat bot solutions in relation to Cognigy and NICE Proactive AI Agent for client implementation projects. • Work as a member of the TTEC Digital project team to enhance and improve software written in JavaScript. • Code and test projects. • Deliver high-quality software on time. • Attend meetings and training as required. • Perform system analysis and project management duties for the successful completion of a project. • Excellent customer-facing presentation skills with the ability to develop new solution pitches, value propositions, and demo experiences. • Exercises wide latitude in determining objectives and approaches to engagements. • Mitigating and resolving code errors for development and future concepts.

Role Description We are looking for a #TechTalent to take on the role of AI Engineer for a project in the logistics sector . - Collaborate with cross-functional teams to identify business needs and potential areas where AI solutions can add value; - Design and develop proof-of-concepts (PoCs) using machine learning and deep learning techniques to demonstrate the feasibility and potential impact of AI-driven solutions; - Evaluate and validate the performance of PoCs, considering factors such as accuracy, scalability, and computational efficiency; - Work closely with stakeholders to understand their feedback and requirements, iterating on PoCs to enhance their value and address specific business challenges; - Analyze the outcomes of PoCs and identify the most promising concepts with significant business value; - Translate successful PoCs into minimum viable products (MVPs), working collaboratively with software engineers and data scientists to productize and scale the solutions; - Optimize and fine-tune AI models and algorithms to meet performance requirements and align with business objectives; - Conduct thorough testing and validation of MVPs, ensuring their reliability, stability, and usability in real-world scenarios; - Collaborate with product teams to integrate AI capabilities into existing systems or develop new AI-driven applications; - Stay informed about industry trends, advancements, and best practices in AI engineering and leverage this knowledge to drive innovation in PoC and MVP development; - Document the development process, methodologies, and results, providing clear and concise reports and presentations to stakeholders; - Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team. Qualifications - Bachelor's or master's degree in computer science, data science, artificial intelligence, Mathematics or a related field; - Proven experience working as an AI Engineer, machine learning engineer, or similar role; - Solid understanding of LLMs, machine learning and deep learning techniques, algorithms, and frameworks (e.g., TensorFlow, PyTorch, Keras, LangChain); - Proficiency in programming languages such as Python and Java, and experience with relevant libraries and tools for data manipulation, analysis, and visualization (e.g., NumPy, pandas, Matplotlib); - Experience with big data processing and distributed computing frameworks (e.g., Hadoop, Spark) is a plus; - Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services; - Strong problem-solving skills and ability to translate business requirements into technical solutions; - Excellent communication and teamwork abilities, with the capacity to collaborate effectively with cross-functional teams; - Strong attention to detail; - A self-driven and proactive attitude, with a passion for learning and staying updated on emerging technologies and industry trends; - Provide technical guidance and support to junior AI engineers, fostering knowledge sharing and continuous learning within the team. Benefits - Opportunity to lead major projects; - Recognition as a professional and as a person; - Work Life Balance and premium benefits; - Possibility to become a shareholder in the company; - Stability and job security; - Fair compensation.

Role Description The AI Engineer is responsible for delivering value through the delivery of AI solutions to core business functions. This role focuses on applying industry AI techniques, tools, and platforms to develop scalable, production-ready systems that solve real business problems. - Own defined initiatives end-to-end, ensuring measurable impact. - Work closely with product, wider engineering teams, and business stakeholders. - Balance technical excellence with strong ways of working. - Contribute to a culture of accountability, trust, and continuous improvement. This role requires strong applied AI engineering skills across architecture, software engineering, and MLOps, combined with the ability to communicate effectively and drive business-aligned outcomes. Qualifications - Strong applied AI engineering skills. - Experience in architecture, software engineering, and MLOps. - Effective communication skills. - Ability to drive business-aligned outcomes. Company Description A global leader in applied safety science, UL Solutions (NYSE: ULS) transforms safety, security and sustainability challenges into opportunities for customers in more than 110 countries. - Delivers testing, inspection and certification services. - Offers software products and advisory offerings that support product innovation and business growth. - The UL Mark serves as a recognized symbol of trust in customers’ products. - Helps customers innovate, launch new products and services, navigate global markets and complex supply chains. - Supports sustainable and responsible growth into the future.

• This is a remote position. • FlexiSAF is a leading EdTech company driving innovation in education across Africa. • Participants will learn to design and build intelligent, LLM-powered applications using modern frameworks such as LangChain, Retrieval-Augmented Generation (RAG) and vector databases. • The program emphasizes practical, project-based learning; from implementing AI-driven workflows and chatbots to integrating models into production-ready applications. • Trainees will also gain exposure to Spring Boot for enterprise API integration and containerization for scalable deployments. • Upon successful completion, participants will be well-positioned to take on AI Engineering roles within any organization building intelligent products and systems.