Manager, GenAI & Cloud Platform, Enablement
Summary
Product manager for Walmart Global eCommerce China owning the GenAI platform and China-local cloud infrastructure strategy — evaluating and governing cloud vendors (Alibaba Cloud, Tencent Cloud, Volcengine), shipping enterprise GenAI use cases (LLMs, RAG, agents), and navigating China AI/cloud regulations while partnering with engineering and global leadership.
About the Role Walmart Global eCommerce China (GEC China) is accelerating its next-generation technology transformation, anchored by Generative AI and a strategic migration to China-local cloud infrastructure. We are looking for an exceptional Product Manager, GenAI & Cloud Platform who sits at the intersection of cutting-edge AI technology, enterprise-scale cloud engineering, and business impact. This is not a theoretical AI role — we need someone who has shipped real GenAI products in enterprise environments, who understands the nuances of the China AI ecosystem (from foundational models to regulatory constraints), and who can navigate complex multi-cloud vendor relationships (Alibaba Cloud, Tencent Cloud, Volcengine, and beyond). You will own the product strategy for our GenAI and cloud platform layer, partnering with engineering, data science, business, and security teams across China and globally.
What You Will Own
• Define and drive the product roadmap for Walmart GEC China's GenAI platform and cloud infrastructure layer.
• Lead cloud vendor evaluation, selection, and governance for China-local cloud (Alibaba Cloud, Tencent Cloud, Volcengine, etc.) and hybrid connectivity with Walmart's global infrastructure.
• Own end-to-end delivery of GenAI use cases — from problem definition, model selection, and RAG architecture design to production deployment and business metric measurement.
• Partner with Walmart's global AI teams to localize and extend GenAI capabilities for the China market, including Chinese LLM integration (Qwen, ERNIE, ChatGLM, etc.). • Lead RFP processes and technical bidding for cloud and AI platform vendors, including security & compliance review (MLPS, PIPL, Walmart SSP).
• Build the internal GenAI platform product — prompt engineering tools, model evaluation frameworks, RAG pipelines, and AI agent orchestration — enabling other product teams to self-serve AI capabilities. • Translate complex technical architectures into executive-facing narratives, business cases, and investment proposals for senior leadership in China and Bentonville.
• Stay ahead of the GenAI landscape — China ecosystem (Baidu, Alibaba, Tencent, ByteDance, Moonshot, Zhipu, MiniMax) and global ecosystem (OpenAI, Anthropic, Google DeepMind, Meta) — and synthesize competitive intelligence into actionable product strategy.
Required Qualifications
1. GenAI Experience — China & Global Ecosystem
• 5+ years of product management experience, with at least 3 years directly focused on AI/ML or GenAI products in enterprise or large-scale consumer platforms.
• Demonstrable track record of shipping GenAI use cases to production in enterprise environments — real, measurable business outcomes (cost reduction, revenue lift, efficiency gains, NPS improvement), not endless pilots.
• Deep hands-on familiarity with core GenAI building blocks: LLMs, Retrieval-Augmented Generation (RAG), vector databases, embedding models, prompt engineering, fine-tuning, and AI agent frameworks.
• Strong understanding of the China GenAI ecosystem: Chinese foundational models (Qwen, ERNIE, ChatGLM, Doubao, Kimi, MiniMax, Yi), their API capabilities, pricing models, strengths, and limitations vs. global alternatives.
• Ability to evaluate and compare Chinese vs. global LLMs for specific enterprise use cases — performance benchmarking, context length, multimodal capability, safety alignment.
• Experience navigating China AI regulatory requirements: data localization, generative AI service regulations, content moderation obligations, and cross-border data transfer constraints under PIPL and DSL.
• Familiarity with enterprise GenAI use case patterns: intelligent customer service, document intelligence, code generation, supply chain optimization, seller/merchant tooling, internal knowledge management, and executive decision support.
• Proven ability to work across China and global teams simultaneously — translating local GenAI needs into global platform contributions and vice versa.
• Experience with model evaluation frameworks: designing eval sets, defining success metrics, A/B testing AI features, and establishing human-in-the-loop feedback loops.
2. Cloud Ecosystem Expertise — China-Local Cloud
• Deep product and commercial expertise in China-local cloud platforms, with hands-on experience across at least two of: Alibaba Cloud (ACK, OSS, MaxCompute, PAI, DashVector), Tencent Cloud (TKE, COS, EMR, TI Platform, Hunyuan), or Volcengine (VKE, TOS, LAS, Doubao Model Suite).
• Understanding of China cloud regulatory requirements: ICP filing (备案), MLPS Level 3 (等保三级), cross-border data transfer gateway, public vs. private cloud trade-offs. • Experience managing cloud vendor RFPs and negotiations at enterprise scale — technical evaluation, pricing benchmarking, SLA design, and contract terms.
• Familiarity with hybrid and multi-cloud architectures connecting China-local infrastructure with global cloud providers (AWS, Azure, GCP) via dedicated lines (专线) or SD-WAN. • Working knowledge of cloud-native categories: managed Kubernetes, serverless, managed databases (OLTP and OLAP), data lake/lakehouse, streaming platforms, CDN, and FinOps tooling.
• Ability to evaluate cloud AI/ML platform services (MaaS, GPU availability, model hosting, AI agent platforms) and translate vendor capability gaps into product requirements. • Understanding of enterprise security on China cloud: VPC isolation, IAM, KMS/HSM, audit logging, vulnerability management, and zero-trust networking.
• Experience with cloud cost governance: FinOps practices, reserved instance strategy, cost allocation, rightsizing, and executive cost reporting.
3. Strong Technical Background — Software Development
• Bachelor's degree or above in Computer Science, Software Engineering, or related technical discipline; Master's degree preferred.
• Minimum 3 years of hands-on software development experience (professional) in backend, platform, or data engineering — able to read and reason about real code, not just diagrams. • Proficiency in at least one modern programming language: Python (strongly preferred for AI/ML context), Java, Go, or Scala.
• Solid understanding of distributed systems fundamentals: microservices architecture, event-driven design, message queues (Kafka/RocketMQ), API design (REST/gRPC), and containerization (Docker/Kubernetes).
• Hands-on experience with the data engineering stack: ETL/ELT pipelines, data warehouse design (OLAP), SQL optimization, and familiarity with open table formats (Iceberg, Hudi, Delta Lake).
• Ability to independently prototype and validate technical concepts — write a quick Python script to test an LLM prompt, query a vector database, or benchmark API latency — without waiting for an engineer. • Comfort with ML/AI engineering concepts: model serving infrastructure, inference latency optimization, token cost management, embedding pipelines, vector similarity search, and LLM evaluation tooling.
• Familiarity with DevOps and CI/CD practices: Git workflows, infrastructure-as-code (Terraform), automated testing, deployment pipelines, and observability.
• Ability to write clear, precise technical product requirements that engineers can implement without extensive back-and-forth — data flow diagrams, API contracts, error handling specs, and non-functional requirements.
4. English Communication — Business & Technical
• Business-level English proficiency (written and spoken) — comfortable presenting to senior Walmart global leadership including VPs and C-suite stakeholders based in Bentonville, San Bruno, or other global offices.
• Proven ability to write executive-quality English documents: strategy memos, business cases, investment proposals, OKR narratives, and board-level presentation decks.
• Experience facilitating cross-cultural, cross-timezone collaboration — running effective meetings with global counterparts, adapting communication style for US vs. China audiences, and managing async communication across significant time zone differences.
• Ability to translate technical complexity into business language in English — making AI architecture choices legible to a CFO, explaining cloud migration risk to a CMO, or presenting model performance to a non-technical board audience.
• Comfort reading and synthesizing English-language technical literature: research papers, cloud vendor documentation, industry analyst reports (Gartner, Forrester, IDC), and open-source project documentation.
• Strong written English for product artifacts: PRDs, user stories, OKRs, quarterly business reviews, and post-mortem reports shared with global product and engineering leaders.
Preferred Qualifications
• Experience at a top-tier technology company (FAANG, BAT, ByteDance, Meituan, JD, Pinduoduo) or a fast-scaling AI startup in a senior product or technical lead role. • Prior experience in e-commerce, marketplace, or retail technology — seller/merchant tooling, supply chain, logistics, or consumer experience platforms. • Familiarity with Walmart's global technology stack, Walmart SSP (Security & Privacy) process, or other Fortune 500 enterprise security frameworks. • Experience with agentic AI frameworks: LangChain, LlamaIndex, AutoGen, CrewAI, Dify, or enterprise agent orchestration platforms. • Track record of building and mentoring cross-functional product teams — coaching junior PMs, running structured product critiques, and establishing PM best practices. • Proficiency in Mandarin Chinese (native or near-native) for collaboration with local engineering and business teams. Walmart doesn’t charge any recruitment or similar fee in the recruitment process, including but not limited to interview, offering, and onboarding.
Skills
- A/B Testing
- Agentic AI
- AI
- Anthropic
- API
- Api Design
- AutoGen
- AWS
- Azure
- CI/CD
- Cloud
- Cloud Native
- Containerization
- CrewAI
- Data Engineering
- Data Lake
- Data Science
- Data Warehousing
- Delta Lake
- DevOps
- Distributed Systems
- Docker
- E-commerce
- ELT
- ETL
- Event Driven Architecture
- Fine Tuning
- FinOps
- GCP
- Generative AI
- Git
- gRPC
- IAM
- Infrastructure as Code
- Java
- Kafka
- Kubernetes
- Lakehouse
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- Microservices
- Model Evaluation
- Networking
- Observability
- OpenAI
- Prompt Engineering
- Python
- RAG
- Scala
- SD-WAN
- Serverless
- SQL
- Terraform
- Test Automation
- User Stories
- Vector Databases
- VPC
- WAN
- Zero Trust