Mô tả công việc:
About KiotViet
KiotViet is Vietnam's largest point-of-sale (POS) provider, serving over 200,000 merchants across a wide
range of industries. For more than 13 years, we have brought the power of technology to businesses of
every size across Vietnam and Southeast Asia through simple, effective solutions - with a particular
focus on supporting micro, small, and medium-sized enterprises.
Today, our team of more than 1,500 people forms the foundation of KiotViet's continued growth. We are
expanding into other Southeast Asian markets with our POS offerings and broadening our product
portfolio into fintech. KiotViet is committed to building a work environment grounded in shared success
and shared responsibility.
Duties and Responsibilities
1. Data & AI Strategy
● Define and execute the company-wide Data & AI strategy, roadmap, and investment priorities
aligned with business objectives.
● Identify opportunities to drive revenue, customer retention, product innovation, and operational
efficiency.
● Establish the KPI framework for Data & AI initiatives, and measure and report business impact
and ROI to leadership on a regular basis.
● Drive internal AI adoption across departments to improve productivity and build an AI-native
way of working company-wide.
2. Data Platform & Architecture
● Lead the development of scalable data architecture, data platforms, analytics infrastructure, and
data governance frameworks.
● Ensure data quality, accessibility, security, and reliability across the organization.
● Build a Single Source of Truth (SSOT) for core business metrics, with clear data ownership,
definitions, and lineage.
● Build a comprehensive, AI-ready metadata and semantic layer that enables secure and
consistent data integration with AI agents and automation tools via protocols such as MCP
(Model Context Protocol), A2A (Agent-to-Agent), and similar standards.
3. AI/ML Innovation & Product Development
● Lead the development and deployment of AI/ML, Generative AI, and AI Agent solutions to
enhance KiotViet's products and internal operations.
● Establish MLOps and LLMOps practices covering model lifecycle management, evaluation
frameworks, monitoring, guardrails, and continuous improvement.
● Deliver scalable, cost-effective AI solutions with measurable business impact.
4. Business Partnership & Performance
● Partner with executive leadership and Product, Engineering, and Business teams to translate
business challenges into data-driven solutions.
● Establish KPIs and measure the business impact and ROI of Data & AI initiatives.
5. Leadership & Governance
● Lead and develop a multidisciplinary team of approximately 30
Data Analysts, Data Engineers,
and
Data Scientists.
● Manage team performance, budgets, technology investments, and cross-functional
collaboration.
● Ensure data governance, privacy, security, and responsible AI practices.
● Lead the adoption of an AI-SDLC (AI-driven Software Development Lifecycle) across the team,
embedding AI coding agents and tools throughout requirements, design, coding, testing, review,
and operations to accelerate delivery while maintaining quality, security, and maintainability