Process Intelligence & AI Enablement Specialist - Operations

Department Operations LevelExperienced (Individual Contributor) LocationManila

The Operation teams at Shopee covers the operational end-to-end process, from when the buyer searches for a product listed on the Shopee platform, to the moment the buyer receives the products. The team analyses and monitors operational KPIs across the region and conducts root cause analysis when operation performance fluctuates. The Operations team comprises Customer Service, Payment, Listings, Warehouse, Logistics, Seller Operations and Fraud.

About the Team: The Process Intelligence & AI Enablement Specialist is responsible for transforming operational processes, policies, and Standard Operating Procedures (SOPs) into structured, scalable, and AI-ready workflows. This role combines process excellence, low-code/no-code solution design, and AI enablement to ensure business processes can be effectively executed by both human teams and AI-powered systems Job Description: 1. Process Mapping & Knowledge Design

• Document, analyze, and improve SOPs, processes, policies, and business rules.
• Create process maps, workflows, decision trees, and AI-ready documentation.
• Define process logic, exception handling, and escalation paths.
• Identify process gaps, risks, and opportunities for improvement.

2. Low-Code / No-Code Workflow Development

• Design and maintain workflows using low-code/no-code platforms.
• Build workflow tools, knowledge repositories, and decision-support solutions.
• Ensure workflows are scalable, user-friendly, and aligned with business needs.
• Translate operational requirements into digital workflows.

3. AI Enablement & LLM Readiness

• Structure knowledge and decision logic for AI and LLM-powered workflows.
• Develop AI-ready frameworks, prompts, and knowledge architecture.
• Identify opportunities for AI adoption and intelligent automation with cross-functional teams.

4. AI Quality Assurance & Audit

• Evaluate AI-generated outputs for accuracy, consistency, and compliance.
• Develop testing standards and quality metrics for AI-assisted processes.
• Monitor AI performance, risks, and support human-in-the-loop improvements.

5. Governance, Monitoring & Continuous Improvement

• Establish governance for process documentation, workflows, and AI solutions.
• Manage version control and change management.
• Track process and AI performance metrics, reporting insights to leadership.
• Drive continuous improvement through data analysis and operational reviews.

6. Stakeholder Collaboration

• Partner with Operations, QA, Training, Product, Policy, and Technology teams.
• Facilitate process discovery and requirements gathering.
• Support onboarding, training, and adoption of workflow and AI solutions.
• Serve as the SME for process optimization and AI-enabled operations.

Requirements:

• Bachelor's Degree in Computer Science, Information Systems, Engineering, Data Science, Business Analytics, Industrial Engineering, or a related field, or equivalent practical experience.
• Minimum of 2–4 years of experience in Process Excellence, Business Process Management, Operations Excellence, Automation, Knowledge Management, or related disciplines.
• Strong experience creating process maps, workflow diagrams, decision trees, and operational documentation.
• Hands-on experience with low-code/no-code platforms, workflow tools, or business process management solutions.
• Familiarity with AI technologies, LLMs, prompt engineering concepts, or AI-assisted workflows.
• Strong analytical, problem-solving, and systems-thinking skills.
• Excellent written, visual, and verbal communication skills.
• Ability to simplify complex operational processes while maintaining accuracy and compliance.
• Experience in e-commerce, logistics, customer support, returns and refunds, trust and safety, or operational excellence environments.
• Experience working with AI-enabled products, conversational AI, knowledge systems, or intelligent automation solutions.
• Familiarity with prompt engineering, AI evaluation frameworks, model testing, annotation workflows, or AI quality assurance methodologies.
• Experience building dashboards, reports, and executive presentations.
• Exposure to AI governance, model monitoring, or responsible AI practices.