Employee Technology & AI Productivity Platform Lead

Job Responsibilities
1. AI Productivity & Agent Platform
1）Define the product and technology strategy and roadmap for the company's AI productivity / Agent platform.
2）Build scalable Agent capabilities including orchestration, tool integration, memory/context management, evaluation, observability, security and governance.
3）Lead teams through 0-to-1 and 1-to-10 product development, rapidly moving high-priority use cases from prototype to production.
4）Establish reusable platform capabilities, engineering standards, connectors and governance rather than allowing individual business units to build fragmented solutions.
5）Identify internally proven capabilities that can potentially be developed into products or platform services for external customers, partners or ecosystems.
2. Employee Technology & Digital Experience
1）Own the end-to-end employee technology experience across collaboration tools, knowledge systems, identity and access, workplace technology, IT service platforms and AI productivity tools.
2）Transform Employee Technology from a traditional operations model into an experience-driven, product-led function.
3）Define the digital employee experience across the full employee lifecycle, from onboarding and daily collaboration through offboarding.
4）Drive adoption, employee experience, self-service and productivity, rather than measuring success only through system availability and operational SLAs.
5）Establish governance for tool selection, integration, renewal and retirement to reduce duplication and fragmentation.
6）Partner closely with Security, Legal, Compliance and Privacy teams to ensure appropriate AI and data governance.
Job Requirements
1. 12+ years of experience in technology product development, platform engineering or related areas.
2. 5+ years leading multiple teams or cross-functional organizations covering engineering, product and platform capabilities.
3. Proven experience building products from 0 to 1 or scaling from 1 to 10, preferably across AI products, Agent platforms, developer tools or productivity SaaS.
4. Strong understanding of Agentic AI / LLM application architecture, including Agent orchestration, RAG, tool/function calling, evaluation, observability and AI guardrails.
5. Strong product and engineering judgment, with the ability to participate meaningfully in architecture and technical trade-off discussions.
6. Experience taking internally developed platforms or tools toward external customers, partners or commercial use is highly preferred.
7. Experience working within complex enterprise environments and balancing speed, security, compliance and scalability.