[AI] AI Agent Application Algorithm Engineer

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Shopee

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Job Description

Job Description

About Us

Sea Group is establishing a brand-new, strategic AI department. This department is dedicated to exploring the transformative potential of generative AI in revolutionizing human connection, self-expression and communication diversity, and social interaction. We are building the next generation of AI-native applications and a comprehensive Model-as-a-Service (MaaS) product support system. Based on massive multi-country data, we are building a leading multilingual AI ecosystem from the ground up. We look forward to more outstanding talents joining us to build leading Southeast Asian multilingual models and explore innovative AI-native applications.

The AI application team focuses on the intersection of social connectivity and artificial intelligence. Our mission is to leverage LLMs to create digital personas that can act as personal assistants and social bridges. This team operates with a startup's agility backed by our Group's robust resources, aiming to define how humans interact in the AI era.

About The Job

  • Agentic Workflow: Design and implement core Agent architectures, including task planning, state tracking, and multi-turn conversation management.
  • Agentic RAG: Architect advanced RAG systems supporting hybrid search (BM25 + Embedding) and LLM-driven proactive retrieval.
  • Memory & Tools: Develop long/short-term memory systems and tool-call/plugin dispatching (ADK framework integration).
  • End-to-End Delivery: Optimize intent recognition accuracy, task completion rates, and system latency for production-grade Agents.

Requirements

  • Master’s in computer science, natural language processing or related fields; Bachelor can be considered with a strong industrial experience.
  • Deep understanding of Agent frameworks (LangChain, LlamaIndex, ADK).
  • Experience in RAG, vector retrieval, and Reranker model optimization.
  • Proficiency in Prompt Engineering and managing LLM capability boundaries.
  • [Plus] Experience in personal assistants or productivity tools (Calendar, Memo, Info-integration).

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