An empowering career at Singtel begins with a Hello. Our purpose, to Empower Every Generation, connects people to the possibilities they need to excel. Every “hello” at Singtel opens doors to new initiatives, growth, and BIG possibilities that takes your career to new heights. So, when you say hello to us, you are really empowered to say…“Hello BIG Possibilities”.

Singtel is where Technology meets Purpose.

We’re building an AI-first telco for the future—connecting people, businesses and communities through trusted networks, intelligent digital services and next-generation technology.

From transforming everyday experiences in mobile, broadband, entertainment and lifestyle services to enabling enterprises with AI, 5G+, cloud, cybersecurity, data centres and digital platforms, we create the technology that powers how millions live, work and connect.

At Singtel, your work creates real impact. You’ll solve meaningful challenges, shape critical digital infrastructure and help build secure, resilient and AI-enabled solutions that serve businesses, digital ecosystems and communities across the globe.

This is where BIG Possibilities become reality. Whether you’re engineering intelligent networks, advancing sovereign AI cloud platforms, strengthening cybersecurity, designing seamless customer experiences or driving sustainable innovation, you’ll be part of teams shaping the future of technology.

Backed by decades of expertise and driven by a culture of continuous learning and innovation, Singtel offers the scale, opportunities and support to help you grow your career while making a difference where it matters most.

Role Summary:

As a Lead AI Platform Architect, you will be the technical authority responsible for defining the architecture, technology strategy and roadmap for Singtel’s enterprise AI platform, including the Central AI Kitchen (CAK) and its supporting AI ecosystem. You will drive the evaluation, adoption and governance of emerging AI technologies, ensuring the platform provides secure, scalable, reusable and enterprise-ready AI capabilities that accelerate AI innovation across the organisation.

Working closely with Enterprise Architecture, AI Platform Engineering, AI Platform Operations, Cybersecurity and business stakeholders, you will define the enterprise AI reference architecture, platform standards, reusable technical frameworks and architectural guardrails that enable consistent and scalable AI solution delivery.

You will provide technical leadership across AI platform strategy, foundation models, agentic AI, model lifecycle management, AI engineering frameworks and platform capabilities, ensuring the AI platform evolves in line with business priorities, technology advancements and enterprise governance requirements.

How You will Make An Impact:

• Define and maintain the enterprise AI platform architecture, technology roadmap and reference architecture for the Central AI Kitchen (CAK) or equivalent AI platforms.
• Establish reusable AI platform capabilities, architectural principles, design standards and technical frameworks to enable secure, scalable and consistent AI adoption across the enterprise.
• Evaluate, benchmark and recommend hosted, self-hosted and open-weight foundation models, defining enterprise model selection strategies based on business, technical and governance requirements.
• Engage with technology partners, cloud providers, AI vendors and the broader technology ecosystem to explore emerging platform capabilities, evaluate new products and identify opportunities to enhance the enterprise AI platform.
• Lead and oversee proof-of-concept (PoC), technology evaluation and pilot initiatives for emerging AI technologies, validating technical feasibility, business value, scalability and enterprise readiness while staying abreast of industry trends and advancements to continuously evolve the AI platform roadmap.
• Establish platform architecture and best practices for model optimisation techniques
• Define the enterprise architecture for multimodal AI capabilities, including language, speech, voice, document, image, vision-language and video models.
• Define enterprise standards and governance for AI model lifecycle management, including model versioning, retraining strategies, regression management, performance evaluation and model retirement.
• Lead technical evaluations, benchmarking and proof-of-concept initiatives for emerging AI technologies, frameworks, platforms and commercial solutions.
• Assess emerging AI technologies and recommend Build, Buy or Partner strategies based on business value, enterprise architecture alignment, scalability and total cost of ownership.
• Publish and maintain AI platform reference architectures, reusable design patterns, technical standards, implementation guidelines and best practices.
• Collaborate with Enterprise Architecture, Cybersecurity and other governance teams to ensure AI platform architecture aligns with enterprise architecture principles, security requirements and regulatory standards.
• Review and govern architecture proposals for new AI platform capabilities, technology adoption and platform enhancements to ensure consistency with enterprise architecture, platform strategy and governance standards.
• Prepare, present and defend AI platform architecture proposals to the Solution Review Board (SRB), senior management and Group/Enterprise Architecture, and seek Architecture Review Board (ARB) clearance, where required, for new platform capabilities, architecture patterns, technology adoption, technology exceptions or enterprise architectural changes.
• Provide architectural direction and technical guidance to AI Platform Engineering teams throughout platform capability planning and implementation.
• Collaborate with AI Platform Engineering and Operation team to define platform observability, operational architecture, reliability requirements and lifecycle management strategies for production AI services.
• Partner with AI Solution Architects to ensure reusable platform capabilities meet evolving business requirements and support scalable AI solution delivery.
• Work closely with AI Security Architects to embed AI security, Responsible AI, privacy and governance requirements into platform architecture and design.
• Mentor Platform Architects and senior technical engineers, fostering architecture excellence, innovation and continuous improvement across the AI platform.
• Serve as the primary technical advisor for enterprise AI platform strategy, engaging senior management, Group/Enterprise Architecture, technology teams and business stakeholders to influence platform direction and drive the continuous evolution of a secure, scalable, interoperable and future-ready AI platform.

Skills for Success:

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, Information Systems or a related technical discipline.
• Strong foundation in enterprise platform architecture, distributed systems and cloud-native technologies.
• At least 10 years of experience in enterprise architecture, platform architecture, software architecture or cloud architecture, designing large-scale enterprise platforms.
• At least 3 years of experience designing AI, Machine Learning or Generative AI platforms in an enterprise environment.
• Proven experience defining platform architecture, technology roadmaps, architecture standards and reusable platform capabilities.
• Experience leading architecture governance, including presenting architecture proposals to senior management and Architecture Review Boards (ARB).
• Experience working across Enterprise Architecture, Engineering, Infrastructure, Cybersecurity, Data and Business teams.
• Strong knowledge of enterprise AI platform architecture, including AI application platforms, AI engineering ecosystems, Model-as-a-Service (MaaS) and agentic AI platforms.
• Strong understanding of foundation models, Large Language Models (LLMs), Small Language Models (SLMs), multimodal AI and enterprise AI deployment strategies.
• Experience defining AI model lifecycle architecture, including model evaluation, fine-tuning strategies, deployment, versioning, monitoring and governance.
• Strong understanding of cloud-native, hybrid cloud and on-premises platform architectures, distributed computing and container orchestration principles.
• Good understanding of enterprise AI application patterns, including Retrieval-Augment
  
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