Key skills
AWSAzureCloudDockerETLFlaskGoogle Cloud PlatformGRPCPythonSQLAILLMRAGLangChainLlamaIndexAnalyticsFastAPIgRPCGCPGoogle CloudVersion ControlCI/CDStakeholder ManagementCommunication
About this role
Role Overview
- Lead the design and hands-on delivery of China AICL capabilities, including AI-ready data products, semantic/consumption layers, and orchestration patterns.
- Translate AI and analytics use-case needs (e.g. DDD) into concrete technical designs and deliverables, moving from PoC or concept into MVP and production-ready solutions.
- Ensure AICL components are usable, stable, and reusable, not just architecturally sound.
- Work day-to-day with Digital/engineering teams to co-design and implement AICL solutions, including integration, deployment, testing, and operational handover.
- Partner closely with Data Science/Digital teams and analytics stakeholders to ensure platform capability aligns with real use cases and adoption pathways.
- Drive the enablement of semantic and context layers as foundational AICL capabilities.
- Guide the design of AI consumption and orchestration patterns as part of AICL L4+ capability planning.
- Responsible for data quality and observability across AICL and related platforms, ensuring enterprise standards and AI/analytics criteria are clearly defined and consistently followed.
- Build training/inference pipelines, packaging, deployment, monitoring, and lifecycle management for models and AI services.
- Proven experience in designing and developing LLM-based applications, including RAG systems and AI Agents.
- Hands-on experience with popular LLM orchestration frameworks such as LangChain, LlamaIndex, or similar tools for building scalable AI solutions.
- Collaborate with Data Scientists to integrate models into scalable services and workflows, enabling repeatable delivery and BAU operations.
- Build and maintain Python services and REST/gRPC APIs that support inference workflows, metadata/services, internal platforms, and automation.
Requirements
- Bachelor’s, Master’s, or PhD in Computer Science, Statistics, Data Science, Engineering, or a related quantitative field.
- 8+ years in data/analytics platforms, dataproduct, or AI enablement roles, with experience leading cross-functional delivery and platform adoption.
- Strong understanding of end-to-end data & AI platform architecture, especially consumption/semantic enablement and platform lifecycle thinking.
- Strong programming skills in Python; experience building backend services with FastAPI/Flask and designing REST APIs.
- Hands-on experience developing ETL pipelines using Python + SQL, working with databases and data modeling concepts.
- Familiar with modern engineering practices (version control, CI/CD concepts, testing, observability), sufficient to lead industrialized delivery with Digital teams.
- Able to evaluate technical options and make pragmatic decisions under China constraints.
- Data Quality & Observability: Experience implementing and managing frameworks for data quality testing, observability, and alerting.
- Strong stakeholder management and communication skills (China + global), able to maintain long-term alignment on platform evolution.
- Experience with cloud platforms and operating services in cloud environments (AWS/Azure/GCP); familiarity with containers (Docker) and CI/CD.
- Strong engineering discipline: testing (unit/integration), code quality, documentation, and operational readiness.
Tech Stack
- AWS
- Azure
- Cloud
- Docker
- ETL
- Flask
- Google Cloud Platform
- GRPC
- Python
- SQL
Benefits
- N/A