The AI Engineer will be a key contributor to Heineken's Global GenAI Lab in Singapore, designing, developing, and implementing end-to-end AI solutions that deliver measurable business impact across the organization. This role combines deep technical expertise in generative AI with strong software engineering skills to build scalable, production-ready systems. You will work as part of a fast-moving technical team with start-up agility within enterprise scale, experimenting with cutting-edge AI technologies while solving real-world business challenges through innovative GenAI applications. The ideal candidate is a versatile engineer who can adapt quickly, think creatively, and become a domain expert while collaborating effectively in a fast-paced, high-impact environment.   Key Responsibilities: AI Solution Development Design and develop GenAI models and applications from concept to production, including model selection, fine-tuning, and optimization for specific business use cases. Build end-to-end AI solutions that integrate seamlessly with existing enterprise systems and workflows. Implement sophisticated prompting strategies and language engineering techniques to maximize model performance and reliability. Create functional demonstration interfaces and prototypes using tools like Gradio, Streamlit, or custom web applications. Stay current with the latest developments in GenAI, including models from OpenAI, Google, Anthropic, and open-weight alternatives. Software Engineering & API Development Build robust, scalable APIs and microservices that serve AI models in production environments. Develop containerized applications using Docker and orchestration platforms for reliable deployment. Create and maintain clean, well-documented code that follows best practices for enterprise software development. Implement proper error handling, logging, and monitoring for AI applications. Collaborate with cross-functional teams using agile development methodologies. Data Pipeline Engineering Design and implement robust data pipelines for preparation, cleaning, and integration of diverse data sources. Handle enterprise data challenges including Excel files, PowerPoint presentations, and Office 365 integrations. Build ETL processes that ensure data quality and consistency for AI model training and inference. Implement data processing solutions that scale efficiently with growing data volumes. Develop data validation and monitoring systems to maintain pipeline reliability. Enterprise Integration & Deployment Integrate AI solutions with existing business systems, databases, and enterprise applications. Navigate complex enterprise environments and work with legacy systems and data formats. Implement security best practices and ensure compliance with enterprise governance requirements. Manage model lifecycle including version control, A/B testing, and performance monitoring. Build solutions that handle enterprise-scale data processing and user loads. Research & Innovation Experiment with emerging GenAI technologies, frameworks, and methodologies Conduct applied research to solve novel business problems using state-of-the-art AI techniques. Evaluate and benchmark different AI models and approaches for specific use cases. Contribute to the lab's knowledge base and share learnings across the team Participate in the broader AI community through conferences, publications, or open-source contributions. Key Requirements: Education: Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related technical field preferred. Strong consideration given to candidates with equivalent practical experience, professional certifications (including AI Singapore certifications), or demonstrated expertise through portfolio work and contributions to AI projects.