Job Summary: 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.

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.

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.

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

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.

Experience:

• 5+ years of software engineering experience with strong proficiency in Python and modern development practices.
• Minimum 2 years of hands-on experience with LLMs, RAG systems, and generative AI applications.
• Proven track record of building and deploying production AI/ML systems in enterprise environments.
• Experience with API development, microservices architecture, and cloud platforms.
• Background in data engineering, ETL processes, and working with enterprise data systems.

Technical Skills - Must have expertise in at least 5 of the following areas:

• GenAI Frameworks: OpenAI API, Anthropic Claude, Google Gemini, Hugging Face transformers, LangChain, LlamaIndex.
• Language Engineering: Advanced prompting techniques, chain-of-thought reasoning, RAG implementation, fine-tuning strategies.
• Software Development: Python, FastAPI/Flask, RESTful APIs, microservices architecture, containerization (Docker).
• Data Engineering: ETL pipelines, data processing frameworks (pandas, dask), database systems (SQL/NoSQL), data quality management.
• Enterprise Integration: Office 365 APIs, SharePoint, Azure/AWS services, enterprise authentication systems.
• MLOps: Model versioning, CI/CD for ML, monitoring and observability, A/B testing frameworks.
• NLP Fundamentals: Text processing, embedding models, semantic search, document parsing and analysis.
• Cloud Platforms: Azure, AWS, or GCP with experience in managed AI services
• Development Tools: Git, JIRA, agile methodologies, code review processes.
• Data Formats: JSON, XML, Excel processing, document parsing, unstructured data handling.

Soft Skills:

• Strong problem-solving abilities with creative approach to technical challenges.
• Excellent collaboration skills and ability to work effectively in cross-functional teams.
• Adaptability and eagerness to learn new technologies and methodologies quickly.
• Self-motivated with ability to work independently while contributing to team objectives.
• Strong communication skills to explain complex technical concepts to non-technical stakeholders.
• Passion for becoming a subject matter expert while maintaining broad technical versatility.
• Entrepreneurial mindset with willingness to experiment and take calculated risks.

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