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Senior AI Solution Architect

Open 24d

Summary

Senior AI Solution Architect designs and deploys enterprise-grade AI systems for Singtel, integrating scalable workflows, hybrid cloud platforms, and LLM-based tools while ensuring security and compliance.

As a Senior AI Solution Architect, you will serve as the technical expert in architecting enterprise-grade and end-to-end AI solutions across Singtel. Working within the AI & Data Analytics (AIDA) business unit, you will drive the design, integration, and deployment of scalable AI workflows that are secure, interoperable, and business-aligned.

This role sits at the intersection of data, platforms and business systems that plays a critical role in translating AI vision into actionable architecture and technical designs. You will collaborate with cross-functional teams across Networks, IT, and external partners to ensure that AI solutions are integrated seamlessly into existing infrastructures and future-ready ecosystems.

How You will Make An Impact:

• Design end-to-end AI solutions that are robust, scalable, and span data ingestion, model deployment, API orchestration, and business system integration across hybrid cloud and on-prem environments

• Architect and deliver solutions for the Central AI platform, encompassing Agentic AI, AI Workbench and Tooling, Model Management, shared RAG service, MCP, AI Runtime environments, etc

• Develop solution blueprinting by translating business needs into technical architecture, including selecting appropriate tools, frameworks, and infrastructure for AI model development and operations

• Integrate AI capabilities with internal APIs, enterprise platforms and user-facing applications in IT and Networks including LLM-based and agentic workflows

• Ensure secure and compliant architecture in collaboration with cybersecurity and governance teams, embedding PDPA and enterprise policy requirements into designs

• Evaluate and recommend AI platforms and tools (e.g. Portkey, Databricks, open-source toolkits) based on enterprise goals and technical fit

• Collaborate with AI engineering and data teams to operationalize AI models, ensuring architectural alignment, scalability, and lifecycle support

• Contribute to proof-of-concepts (PoCs), technical evaluations, and prototyping efforts under supervision

• Stay current with AI technologies and best practices in integration, model lifecycle management, and platform operations

• Participate in architecture reviews, technical discussions, and sprint planning with cross-functional teams.

• Define and enforce architectural standards, reusable design patterns, open-standard, and reference implementations to streamline AI deployment across business units

• Provide technical leadership in prototyping, experimentation, vendor technology evaluations, and innovation pilots

• Stay updated on emerging AI technologies such as vector databases, context-aware agents, orchestration protocols (e.g. LangChain, LangGraph, MCP, A2A, etc) and assess their applicability within the enterprise

• Responsible for leading solutioning activities and managing a small development team consists of AI engineer and application developer for selected use cases

Skills for Success:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data, AI/ML, or related field.

• 3 to 5 years of experience in solution architecture in AI/ML platform integration, data pipeline design and API-driven systems

• Proven expertise in designing and integrating end-to-end AI workflows, including data pipelines, model orchestration, and serving APIs across hybrid cloud environments

Good to have:

• Certification on Microsoft Azure, AWS, GCP or Databricks.

• More than 5 years of experience in enterprise architecture.

• Proven experience working in a telco environment or implementing AI platforms on-premise or in the cloud (e.g., Microsoft Azure, AWS, etc.).

• Experience with on-premise data lake platforms such as Cloudera and HPE Ezmeral.

See also

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