Manage the AI Platform team cluster directly: AI Platform Engineer, AI Data Architect, and LLM Ops / MLOps Engineer
Provide technical direction and functional oversight to the AI Data Architect on AI data foundation design — embedding strategy, vector DB design, knowledge graph ingestion approach
Coordinate with the Applied AI cluster on technical requirements for use case delivery and review Applied AI Engineers' architecturally significant decisions
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Facilitate workshops and meetings to discuss process improvements and gather feedback from internal stakeholders.
Be a focal point for the customer’s operational and technical needs and become a trusted advisor with customers by deeply understanding their network and aligning their needs with Singtel solutions.
Act as a customer advocate internally while effectively collaborating with internal teams including Technical Assistance Center, product management, engineering, pre-sales and quality management.
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Ensure the HIE architecture effectively supports advanced features like population health analytics and AI/ML initiatives by harmonizing data in the SDA structure.
Establish and enforce development, configuration, and security standards for all HealthShare integrations and custom applications.
Oversee and guide the development teams on best practices for ObjectScript, DTL, XSLT, and BPL development within the Interoperability Production environment.
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• You are expected to be a subject matter expert, collaborate and manage the team to perform effectively, and be responsible for team decisions.
• Engaging with multiple teams and contributing to key decisions will be essential, as well as providing solutions to problems that apply across various teams.
• Expert proficiency in Cloud Platform Architecture is required. Expert proficiency in Applications Architecture is recommended. Additionally, expert proficiency in Cloud Management Platform and Cloud Enterprise Architecture is suggested.
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Codebase Handover: Facilitate the seamless handover of the finalized codebase to centralized, operations-driven technology teams, ensuring pristine code quality, proper containerization, and long-term deployment readiness.
A minimum of 5 years of applied experience in software engineering, highly technical support, or complex solutions engineering.
At least 2 years focused exclusively on deploying machine learning (ML) or natural language processing (NLP) applications in live commercial environments.
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Develop thought leadership content—demo templates, whitepapers, enablement sessions—focused on agent lifecycle, integration strategy, and technical effectiveness.
Act as a central technical knowledge resource, proactively addressing internal technical inquiries, facilitating deep technical enablement, and documenting best practices to empower specialist teams across the organization.
Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.
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Develop thought leadership content—demo templates, whitepapers, enablement sessions—focused on agent lifecycle, integration strategy, and technical effectiveness.
Act as a central technical knowledge resource, proactively addressing internal technical inquiries, facilitating deep technical enablement, and documenting best practices to empower specialist teams across the organization.
Understand Agent Interoperability - Map and integrate external agents from hyperscalers (e.g. Copilot, Gemini) into Agentforce via open standards (MCP, A2A); design how these systems collaborate.
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· Create high-level and low-level designs, reference architectures, migration roadmaps, operational runbooks, and transition plans.
· Act as a hands-on architect for infrastructure, cloud landing zones, network connectivity, security controls, identity, backup, monitoring, and automation.
· Assess current-state IT landscapes and define target-state hybrid cloud solutions aligned to business, technical, security, compliance, and cost objectives.
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Ensure the HIE architecture effectively supports advanced features like population health analytics and AI/ML initiatives by harmonizing data in the SDA structure.
Establish and enforce development, configuration, and security standards for all HealthShare integrations and custom applications.
Oversee and guide the development teams on best practices for ObjectScript, DTL, XSLT, and BPL development within the Interoperability Production environment.
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