Backend Engineer - Search, Ads & Recommendation Mandarin Required

Key Responsibilities:

Search, Ads & Recommendation Backend Engineering
- Design, build, and continuously optimize the core engine and business architecture powering Search, Advertising, and Recommendation.
- Build systems supporting both the company's main platform and international product.
- Develop highly scalable online services capable of supporting tens to hundreds of millions of users.

AI-Native Application Engineering
- Lead the productionization of LLM and multimodal capabilities across Search, Recommendation, and Advertising.
- Own service design, backend development, end-to-end latency optimization, and system performance optimization.
- Build production-grade AI applications and infrastructure involving LLM-powered features, RAG pipelines, agent workflows, prompt engineering, and systematic LLM pipelines.
- Ensure AI-powered systems operate reliably and efficiently at scale.

Model-to-Product Architecture
- Build the engineering bridge between model capabilities and real-world product experiences.
- Work closely with algorithm and machine learning teams to bring model capabilities into production.
- Design backend systems capable of supporting large-scale online Search, Ads, and Recommendation workloads.
- Optimize end-to-end architecture for high concurrency, high availability, low latency, scalability, and production reliability.

Shared Framework & Platform Development
- Design and abstract shared engineering frameworks and platform components for reuse across multiple business lines.
- Reduce duplicated engineering work across Search, Recommendation, and Ads.
- Improve overall engineering efficiency, system quality, and maintainability.
- Identify architectural risks early and proactively drive technical solutions through to production.

Requirements:

Education & Experience
- Bachelor’s degree or above in Computer Science or a related field, or equivalent practical experience.
- Minimum 3+ years of experience building large-scale backend systems and distributed systems.

Programming & Engineering Fundamentals
- Proficient in at least one of: Java, C, or C++.
- Strong software engineering fundamentals.
- High standards for code quality, system design, and engineering discipline.

Distributed Systems Expertise
- Deep understanding of high-concurrency distributed systems, high-availability architecture, and large-scale system design.
- Strong practical experience in system scalability, performance optimization, and latency optimization.
- Mature methodology for identifying and resolving scalability and performance bottlenecks.

Production LLM / AI Engineering
- Hands-on experience putting LLMs into production.
- Practical experience with one or more of: RAG, agents/agent workflows, prompt engineering, systematic LLM pipeline development.
- Ability to combine AI capabilities with Search, Advertising, and Recommendation products.
- Experience designing reliable production systems around LLM or multimodal capabilities.

Large-Scale Architecture & System Ownership
- Experience developing products or systems serving tens of millions of users.
- Ability to independently own architecture design, key domain modeling, and critical backend systems.
- Strong system abstraction and architecture design capabilities.
- Ability to identify architectural risks early and proactively drive them to resolution.

Ownership & Collaboration
- Strong business awareness and technical judgment.
- Strong sense of ownership and ability to independently drive complex technical projects.
- Effective cross-team collaborator.
- Comfortable working closely with algorithm engineers, machine learning teams, product teams, and backend engineering teams.

Language Requirements
- Proficiency in both Mandarin Chinese and English is mandatory
- Comfortable collaborating across globally distributed engineering teams.

Nice to Have:
- Experience building or operating large-scale Search, Advertising, or Recommendation systems.
- Experience supporting international products or overseas engineering projects.

Why This Role:
- Build core Search, Recommendation, and Advertising systems for a global consumer platform at massive scale.
- Work on high-concurrency, highly available distributed systems serving tens of millions of users.
- Bring LLM and multimodal capabilities into real-world production environments.
- Work directly at the intersection of backend engineering, AI, and Search/Recommendation/Ads.
- Collaborate closely with algorithm and machine learning teams.
- Join the company's US engineering organization at an early stage and take significant technical ownership as the team expands.

*Unfortunately, only shortlisted candidates will be contacted.

EA Licence No.: 25S3232
EA Personnel Reg. No.: R1874604
EA Personnel Name: Kenneth Ho