[What the role is]

About IMDA:
The Infocomm Media Development Authority (IMDA) spearheads Singapore’s digital transformation by building a vibrant digital economy and an inclusive digital society. As an Architect of Singapore’s Digital Future, IMDA drives innovative initiatives that empower both public and private sectors to harness emerging technologies.

Position Overview:
The Technical Manager (Generative AI) will lead the technical development and integration of applications with a focus on generative AI capabilities. This role combines traditional application development oversight with cutting-edge AI implementation, ensuring robust, scalable, and innovative solutions for enterprise platforms.

[What you will be working on]

Responsibilities:

Application Development & AI Integration:

• Lead the technical architecture and development of applications, incorporating generative AI features where beneficial
• Design and implement robust AI pipelines for text, image, and code generation capabilities
• Develop and maintain prompt engineering frameworks and best practices
• Oversee the integration of multiple AI models and APIs while ensuring optimal performance and cost efficiency
• Establish technical standards for responsible AI development, including bias detection and mitigation strategies

Technical Leadership:

• Guide development teams in building and maintaining applications with AI capabilities
• Evaluate and recommend appropriate AI models, frameworks, and tools
• Implement AI governance frameworks and ethical guidelines
• Ensure applications meet security requirements, performance standards, and compliance guidelines
• Lead AI model evaluation, fine-tuning, and deployment processes

Project Management:

• Manage the full application development lifecycle, from requirements gathering to deployment and maintenance
• Coordinate with cross-functional teams to deliver projects on schedule and within budget
• Implement agile methodologies and MLOps practices to improve development efficiency

Innovation & Technical Strategy:

• Identify opportunities to enhance applications through generative AI features
• Develop technical roadmaps for application modernisation and AI integration
• Research and evaluate emerging AI technologies and their potential applications
• Design strategies for AI model versioning, monitoring, and maintenance

Stakeholder Management:

• Collaborate with business units to understand requirements and translate them into technical specifications
• Communicate technical concepts and project progress to various stakeholders
• Work with vendors and partners to ensure successful implementation of solutions

[What we are looking for]

Requirements:

Educational Background:

• Degree in Computer Science, Software Engineering, Artificial Intelligence, or related technical field
• Professional certifications in AI/ML technologies are advantageous

Technical Expertise:

• 5+ years of experience in application development and technical team management
• Minimum 2 years of hands-on experience with generative AI technologies
• Demonstrated expertise in:
  • Large Language Models (LLMs) and their applications
  • Prompt engineering and chain-of-thought implementations
  • Vector databases and embedding technologies
  • AI model fine-tuning and deployment
  • RAG (Retrieval-Augmented Generation) architectures
• Strong background in software architecture and system design
• Proficiency in Python and modern development frameworks
• Experience with AI/ML platforms (e.g., OpenAI, Anthropic, Hugging Face)
• Knowledge of cloud platforms (AWS, GCP, Azure) and containerisation technologies
• Understanding of API design, microservices architecture, and system integration

Leadership & Professional Skills:

• Proven track record of leading technical teams and managing complex AI projects
• Strong problem-solving abilities and analytical thinking
• Experience in AI governance and ethical considerations
• Excellent communication skills and ability to work with diverse stakeholders
• Experience in agile methodologies and MLOps practices
• Understanding of government digital services is preferred

Additional AI Experience:

• Experience with multimodal AI systems (text, image, audio)
• Knowledge of AI safety and security best practices
• Familiarity with AI model evaluation metrics and performance optimization
• Understanding of AI infrastructure scaling and cost management
• Experience with AI-specific testing and quality assurance methodologies

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