Senior Manager / Manager, Digital Transformation & Generative AI Innovation

[What the role is]

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.

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]

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

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

[What we are looking for]

Only shortlisted applicants will be notified.

Position will commensurate with experience.