Senior AI Ecosystem Intelligence & Automation Architect

Intel; Seberang Perai; On-site; MYR 180,000 - 300,000; Full time

Job summary

Intel in Malaysia seeks a Senior AI Ecosystem Intelligence & Automation Architect to design and operationalize AI-enabled capabilities that scale, improve accuracy, and automate ecosystem programs across discovery, onboarding, qualification, catalog operations, partner engagement, and reporting.

You will shape data architecture, metadata, and AI-assisted workflows to deliver trusted intelligence and repeatable processes.

Qualifications

• Bachelor degree or equivalent practical experience in computer science, information systems, AI/ML, data analytics, digital platforms, product operations, or a related field.
• 3+ years of experience in AI-enabled platforms, data architecture, automation, analytics, enterprise search, reporting, digital operations, or technical program enablement.
• Experience defining requirements for data extraction, metadata, reporting, dashboards, search, analytics, workflow automation, or AI-enabled digital capabilities.
• Strong understanding of how AI, structured data, taxonomy, metadata, analytics, and automated workflows can improve operational sc

Responsibilities

• Focus on information architecture, metadata, taxonomy, search optimization, knowledge management, and AI/RAG readiness to support the organization's AI-driven discovery and ecosystem platform strategy.
• Design AI-enabled operational capabilities that automate manual ecosystem program workflows, including intake, onboarding, validation, status collection, content classification, and reporting preparation.
• Define ecosystem data and metadata requirements that support accurate search, filtering, recommendations, customer-facing discovery, internal reporting, and AI-assisted workflows.
• Architect data extraction and normalization approaches that convert partner, program, catalog, qualification, and engagement data into usable ecosystem intelligence.
• Develop requirements for AI-powered search, recommendations, chatbot assistance , RAG-ready content structures, guided workflows, and agentic process automation.
• Create operational reporting requirements and dashboards for ecosystem engagement, customer satisfaction, onboarding health, qualification status, content quality, and program execution visibility.
• Identify opportunities to use AI to reduce manual effort, eliminate repeat work, improve data quality, accelerate customer response, and scale ecosystem program operations.
• Partner with UX, program operations, ecosystem strategy, and development teams to ensure AI-enabled operational capabilities are grounded in real user journeys and program execution needs.
• Work with development teams to translate AI, automation, data, and reporting requirements into buildable specifications, acceptance criteria, and quality expectations.
• Establish data quality checks, automation rules, and operational feedback loops that keep ecosystem information correct, current, searchable, and decision-ready .
• Analyze customer engagement, search behavior, satisfaction signals, and operational process data to recommend improvements to ecosystem experiences and workflows.

Skills

AI-enabled platforms

Data architecture

Automation

Analytics

Enterprise search

Reporting

Digital operations

Program enablement

UX collaboration

Metadata management

Education

Bachelor degree or equivalent in CS / IS / AI/ML / data analytics

Job description

Job Details

Job Description

The Senior AI Ecosystem Intelligence & Automation Architect will design and operationalize AI-enabled capabilities that improve the scalability, accuracy, discoverability, reporting, and operational efficiency of Intel Edge AI and Robotics ecosystem programs. The role uses AI, data architecture, metadata, data extraction, analytics, and automation to turn ecosystem program activity into trusted operational intelligence and repeatable workflows.

The successful candidate will help build the intelligence and automation layer supporting ecosystem programs, customer discovery, onboarding, qualification, catalog operations, partner engagement, and internal reporting. This includes automated intake and validation workflows, ecosystem data extraction and normalization, AI-powered search and recommendations, customer satisfaction insights, operational dashboards, and AI-assisted reporting that supports both internal stakeholders and external customer experiences.

This role is expected to work as part of a central design and operations team where UX, program operations, ecosystem strategy, AI enablement, and development execution must connect. The role is not limited to AI feature design. Its primary purpose is to make ecosystem operations more scalable, measurable, automated, and customer-responsive through applied AI and trusted data.

Key Responsibilities

• Focus on information architecture, metadata, taxonomy, search optimization, knowledge management, and AI/RAG readiness to support the organization's AI-driven discovery and ecosystem platform strategy.
• Design AI-enabled operational capabilities that automate manual ecosystem program workflows, including intake, onboarding, validation, status collection, content classification, and reporting preparation.
• Define ecosystem data and metadata requirements that support accurate search, filtering, recommendations, customer-facing discovery, internal reporting, and AI-assisted workflows.
• Architect data extraction and normalization approaches that convert partner, program, catalog, qualification, and engagement data into usable ecosystem intelligence.
• Develop requirements for AI-powered search, recommendations, chatbot assistance , RAG-ready content structures, guided workflows, and agentic process automation.
• Create operational reporting requirements and dashboards for ecosystem engagement, customer satisfaction, onboarding health, qualification status, content quality, and program execution visibility.
• Identify opportunities to use AI to reduce manual effort, eliminate repeat work, improve data quality, accelerate customer response, and scale ecosystem program operations.
• Partner with UX, program operations, ecosystem strategy, and development teams to ensure AI-enabled operational capabilities are grounded in real user journeys and program execution needs.
• Work with development teams to translate AI, automation, data, and reporting requirements into buildable specifications, acceptance criteria, and quality expectations.
• Establish data quality checks, automation rules, and operational feedback loops that keep ecosystem information correct, current, searchable, and decision-ready .
• Analyze customer engagement, search behavior, satisfaction signals, and operational process data to recommend improvements to ecosystem experiences and workflows.

AI-Centered Operational Deliverables

• AI-assisted ecosystem search and recommendation requirements that improve internal and external discovery.
• Automated data extraction and normalization requirements for catalog, qualification, partner, and ecosystem program inputs.
• Operational automation requirements for intake validation, onboarding readiness, lifecycle tracking, and program status collection.
• Customer satisfaction and engagement intelligence requirements that identify friction, gaps, and improvement opportunities.
• Ecosystem reporting framework covering program health, customer usage, qualification status, content quality, and operational performance.
• Data quality and governance rules that ensure AI outputs, search results, dashboards, and customer-facing ecosystem information stay reliable.
• AI-enabled self-service and workflow recommendations that reduce manual support and improve customer completion rates.

Qualifications

• Minimum Qualifications
• Bachelor degree or equivalent practical experience in computer science, information systems, AI/ML, data analytics, digital platforms, product operations, or a related field.
• 3+ years of experience in AI-enabled platforms, data architecture, automation, analytics, enterprise search, reporting, digital operations, or technical program enablement.
• Experience defining requirements for data extraction, metadata, reporting, dashboards, search, analytics, workflow automation, or AI-enabled digital capabilities.
• Strong understanding of how AI, structured data, taxonomy, metadata, analytics, and automated workflows can improve operational sc