(Chinese Mainland) Campus Recruiting - Information Technology Manager

Description:

• At P&G, we use data and technology to solve challenges range from developing creative products, personalizing consumer experiences, go-to-market efficiency, and organization efficiency.
• P&G Information Technology (IT) mission is to enable company to win consumer, customer, and employee with forward looking AI/Agent & data strategy, capabilities and innovations.
• A career in P&G Information Technology (IT) builds depth of technical mastery, leadership and influence skills, breadth of experience across business domains and roles, and networking with China/global giant players and ecosystem like Ali, Tencent, ByteDance, JD, Microsoft etc.
• We develop the future CIO/CDO/CTO/CISO for consumer goods and retail industry, and the technical innovation game changers for new decades with AI/Agent and Data expertise.

Full Stack Software Engineer (AI Agent)

As a Campus Full Stack Engineer (AI Agent), your core work is building AI-powered solutions and AI agents — from LLM integration, prompt design, tool/function calling, to RAG and multi-agent collaboration — turning large-model capabilities into agents that are genuinely usable, production-ready, and valuable to the business. You'll do full-stack development (backend services, APIs, and web front-end) along the way, but that's in service of the agents you build: what you're really doing is putting AI into production, making agents work, and moving the business because of it. You work in a small Agile/DevOps team, make extensive use of AI-assisted development across the full SDLC, and take ownership of items in the Sprint Backlog.

• Build and iterate on AI agents and AI-powered features — LLM integration, prompt engineering, tool/function calling, RAG, and multi-agent orchestration — for platform capabilities or global digital products. This is your main arena.
• Turn agents into real products: design and implement the backend services, APIs and web front-end that power them, and integrate with enterprise systems and our enterprise-grade AI agent platform.
• Use AI coding tools (Copilot / Codex / Claude), leading Chinese LLMs (DeepSeek / Qwen / Kimi / Seedance / GLM), and vibe coding as a daily part of your workflow.
• Work in a Scrum team; write clean, tested code; participate in code reviews and continuous delivery.
• Collaborate with product, UED, testing and operations to deliver AI value to the business faster.

• Proficient in Python, the primary language for AI/agent/Machine Learning development.
• Proficient with at least one AI coding tool (Copilot, Codex, Claude) in your development workflow; familiarity with leading Chinese LLMs (e.g. DeepSeek, Qwen, Kimi, Seedance, GLM) is a plus.
• Hands-on experience building AI-powered applications or AI agents — e.g. LLM integration, prompt engineering, function/tool calling, or RAG — through internships, projects, hackathons, coursework or open source. A strong interest and demonstrated ability to learn in this area is essential.
• Solid programming fundamentals: data structures, algorithms, and basic web/backend concepts (HTTP, REST APIs).
• Basic knowledge of SQL and/or NoSQL databases (e.g. MySQL, PostgreSQL, Redis, Elasticsearch, MongoDB).

The core mission is to ensure data flows reliable, governable, and at scale across the entire lifecycle from source to consumption and empowering a wide range of AI and BI business scenarios. You will own end-to-end management of data ingestion, processing, and publication, while working closely with business units to build data analytics products that truly drive decision-making and execution.

This full-stack role integrates expertise in Data Modeling, Data Architecture, Data Pipeline Engineering (ETL/ELT), and Data Product development with below responsibilities & development:

Data Engineering

• From Ingestion to Publication
• Own the end-to-end lifecycle of one or more data pipelines—covering ingestion, cleansing, transformation, publication, and operations.
• Design data models and data signals—collaborating with business users and data teams to analyze requirements and use cases, and to architect high-quality analytical datasets.
• Build high-performance ELT applications on data lake/warehouse platforms using big data technologies such as Apache Spark and Databricks.
• Integrate diverse data sources (e.g., SAP, Oracle, MySQL, Azure Blob/ADLS) and build robust data integration solutions.
• Develop data orchestration workflows (Apache Airflow / Azure Data Factory) and CI/CD pipelines (GitHub Actions).

• Empowering Business
• Deep dive into business contexts (Marketing, Sales, Supply Chain, etc.) to understand needs and build data analytics products for business users.
• Develop BI+AI solutions (Power BI / custom visualizations) to present complex backend data in intuitive, accessible formats.
• Design data publishing and consumption interfaces, enabling AI Agents, ML models, and BI reports to access high-quality data seamlessly.

• Establish data quality checks and monitoring mechanisms to ensure pipeline reliability and trust in data assets.
• Drive the adoption of data platform best practices—including data testing, publishing standards, and operational guidelines.

• Strong Python & SQL skills as the core toolset for data engineering, with a focus on writing clean, maintainable code.
• Hands-on data experience and showcased through projects, internships, or competitions in data processing, analytics, or modeling.
• Knowledge of data modeling familiarity with relational databases, ER diagrams, and dimensional modeling (Star/Snowflake Schemas).
• Basic software engineering practices with proficiency in Git, testing, and RESTful API design.

AIE role drives the development of our enterprise AI Factory, building core platform infrastructure (Gateways, Sandbox Runtimes, Orchestration, and Observability) to democratize AI Agent creation. Own the operationalization of ML models and Agents, scaling prototypes into production-grade systems that generate real business impact.

You won’t just be writing code - you will build the engine that powers AI across the enterprise.

Direction 1: AI Factory Platform Development

• Designed and developed core components of an enterprise-grade AI Agent platform, including the LLM Gateway, Agent Sandbox Runtime, tool registration & orchestration, and monitoring & observability stacks.
• Established robust identity, permission, and governance frameworks to ensure enterprise-level security and compliance.
• Developed platform SDKs, CLI tools, and developer utilities to lower the barrier to entry for AI Agent development across the organization.
• Built end-to-end MLOps/AgentOps pipelines, covering model registry, automated testing, canary deployments, and rollback strategies.

• Operationalized machine learning models and AI Agents developed by data science teams—focusing on performance optimization, containerization, API encapsulation, and production deployment.
• Constructed data pipelines and feature engineering platforms to support model training and inference workflows.
• Collaborated closely with business and data science teams to deliver end-to-end AI-driven solutions (e.g., Supply Chain, Marketing, Sales).
• Implemented continuous monitoring of production AI systems to track health metrics and drive iterative improvements.

• Proficient in Python — the language of choice for AI/ML engineering. Experienced in package development and core data processing libraries (pandas, NumPy, scikit-learn), with a proven ability to write clean, testable code.
• Genuine interest and hands-on experience in AI/ML — demonstrated through coursework, competitions, hackathons, internships, or open-source contributions. You don’t need to be an expert today, but you should be able to showcase what you’ve built and what you’ve learned.
• Foundational software engineering knowledge — understanding of object-oriented programming, testing, version control (Git), and REST APIs.
• Exposure to at least one cloud platform (Azure, Alibaba Cloud, GCP, AWS, etc.), or demonstrated ability to learn new platforms quickly.
• Proficient in SQL and fundamental data management concepts.

• At least a bachelor's degree.
• Majored in STEM with Software Engineering/Development, Computer Science, AI, Machine Learning, LLM, Data Science, Mathematics, Statistics.
• Basic knowledge of SQL and/or NoSQL databases (e.g. MySQL, PostgreSQL, Redis, Elasticsearch, MongoDB).
• Strong enthusiasm and curiosity about the intersection of business and AI/Data technology.
• Good Leadership, communication and problem-solving Skills.

Guangzhou

Interview City:

Guangzhou/Online

※ You could apply one or two requisitions and identify it as “First Choice” or “Second Choice”. Once you submit your application, your choices will be finalized and cannot be changed.