Enterprise AI Architect

ORANGE BUSINESS SERVICES SINGAPORE PTE. LTD.; Singapore; On-site; SGD 180,000 - 300,000; Full time

Job summary

ORANGE BUSINESS SERVICES SINGAPORE PTE. LTD. seeks an Enterprise AI Architect to serve as the primary technical authority for end-to-end AI ecosystems, bridging core infrastructure with the AI Knowledge Layer.

You will lead architectural strategy for MaaS and GenAI, delivering repeatable, globally deliverable services. The role requires extensive experience in AI platform architecture, distributed systems, and regional GTM leadership in APAC, translating technical capabilities into compelling

Qualifications

• Proven experience in Data & AI Platform Architecture.
• Experience with distributed systems and modern data stacks for global deployments.
• Expertise in AI/ML infrastructure and models from major providers.
• Experience with MongoDB and Snowflake as foundational components.
• APAC region experience with stakeholder management.

Responsibilities

• Full-Stack AI Architecture Design: Architect AI platforms spanning training, inference, and data pipelines across core, cloud, and edge environments.
• Design the AI Knowledge Layer, integrating object storage, vector databases, and lakehouse architectures to support RAG and enterprise search.
• Define reference architectures for MaaS and AI workload placement based on latency, resilience, and scale.
• Translate complex AI platform capabilities into customer-ready solutions and deployable service blueprints.
• Collaborate with infrastructure and network engineers to align AI platforms with enterprise delivery models.
• Develop application-level AI frameworks, guiding the integration of LLMs into enterprise software and workflows.
• Act as architectural anchor for regional GTM initiatives, translating technical capabilities into value propositions for enterprise customers.
• Guide specialist engineering teams toward integrated outcomes for GenAI and related domains.
• Support enterprise pursuits by aligning technical intent with commercial viability and long-term scalability.

Skills

AI Platform Architecture

Distributed Systems

APAC Experience

Strategic Leadership

LLM Integration

OpenAI/Anthropic/Google models

MongoDB

Snowflake

Tools

MongoDB

Snowflake

Job description

As anEnterprise AI Architect, you will serve as the primary technical authority for designing and commercializing end-to-end AI ecosystems. This role focuses on bridging the gap between core infrastructure and the high-levelAI Knowledge Layer, ensuring that models, data pipelines, and applications are integrated into repeatable, globally deliverable services. You will lead the architectural strategy for shifting from traditional storage andcomputeto sophisticatedModel AI (MaaS)andAgentic AIframeworks.

Key Responsibilities

• Full-Stack AI Architecture Design:

• Architect comprehensive AI platforms spanningtraining, inference, and data pipelinesacross core, cloud, and edge environments.

• Design theAI Knowledge Layer, integrating object storage, vector databases, andlakehousearchitectures to support RAG (Retrieval-Augmented Generation) and enterprise search.

• Define reference architectures forModel-as-a-Service (MaaS)and the placement of AI workloads based on latency, resilience, and scale.

• Solution Engineering & Service Blueprints:

• Translate complex AI platform capabilities intocustomer-ready solutionsand deployable service blueprints.

• Collaborate with infrastructure and network engineers to ensure AI platforms align with existing enterprise operational and delivery models.

• Developapplication-level AI frameworks, guiding the integration of LLMs into functional enterprise software and workflows.

• Technical GTM & Strategic Leadership:

• Act as thearchitectural anchorfor regional GTM initiatives, translating deep technical AI capabilities into clear value propositions for enterprise customers.

• Guide specialist engineering teams toward integrated outcomes, enabling them to execute confidently innew technologydomains likeGenAI.

• Support high-stakes enterprise pursuits by aligning technical intent with commercial viability and long-term scalability.

Required Qualifications

• Architectural Expertise:

• Proven experience inData & AI Platform Architecture, including deep knowledge of distributed systems and modern data stacks.

• Significant background in architecting forperformance, resilience, and scalabilitywithin global serviceprovideror large enterprise environments.

• AI/ML Domain Knowledge:

• Advanced understanding ofAI/ML infrastructure, including experience with leading models from OpenAI, Anthropic, or Google.

• Expertiseindatabase technologies(e.g., MongoDB, Snowflake) as foundational components for AI solution stacks.

• Strategic Regional Focus:

• Extensive professional history within theAPAC region, managing complex stakeholder environments and cross-functional teams.

• A track recordof driving technical strategy for high-growth business units in the cloud and data sectors.