Senior Manager (AI Engineer) - Future Capabilities

About the role

The Senior Manager (AI Engineer) oversees the delivery of cutting-edge artificial intelligence and machine learning products from conception to deployment. The role combines technical expertise in AI/ML with product management skills, and involves defining, developing and deploying AI/ML solutions that solve business problems.

Key responsibilities

• Translate complex AI/ML concepts and requirements into detailed project plans.
• Apply supervised or unsupervised machine learning algorithms and understand the trade-offs for each data problem.
• Define the tools needed for product development and advise the organisation on suitable development environments.
• Analyse engineering trade-offs and explain technical decisions to the wider team.
• Implement safeguards and controls for AI-generated content.
• Collaborate with data scientists, engineers, product owners and stakeholders to define product requirements and roadmaps.
• Document workflows and maintain reproducibility of AI pipelines.
• Ensure compliance with Singapore Government security and data governance standards.

Required profile

• Bachelor's degree in computer science, information technology or a related field in data science, ML or AI.
• Proven experience delivering AI/ML products or projects and building products with modern AI/ML frameworks and GenAI tools.
• Strong project management, analytical and problem-solving skills, and excellent communication and teamwork skills.
• Pass the online technical assessment administered by the Government Technology Agency's Digital Academy and submit the results to BCA as part of the recruitment process.
• PMP, Agile, Scrum or similar certification is a plus; a passion for AI/ML and high personal integrity are also valued.

Required skills

• Modern AI/ML frameworks such as PyTorch, TensorFlow and Hugging Face, including GenAI tools.
• Familiarity with AI orchestration frameworks such as LangChain, LlamaIndex and CrewAI.
• Machine learning algorithms, data structures, software development principles (frontend and backend), Retrieval-Augmented Generation and agentic AI.
• Knowledge of responsible AI principles and ethical considerations.