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Superintelligence Lab - Tech Lead (Agentic Search, Staff / Principal Level)LG AI Research · Gangseo-gu, Seoul, South Korea

LG AI Research

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Superintelligence Lab - Tech Lead (Agentic Search, Staff / Principal Level)

🗓️ Posted 2026-09-28 Gangseo-gu, Seoul, South Korea Hybrid ICT
💰 Salary Not shared 📊 Market 10,000,000 KRW–18,000,000 KRW/mo

About the Role

우리는 사용자의 의도를 이해하고, 필요한 정보를 탐색 검증 종합하여 신뢰할 수 있는 결과를 만들어내는 agentic search system을 구축하고 있습니다. 혁신적인 retriever 학습, agentic 시스템 설계, memory/context 최적화, orchestrator RL학습, evaluation, inference efficiency까지 전체 기술 방향과 프로젝트를 이끄는 Senior Tech Lead 포지션입니다. Staff / Principal-level MTS로서 장기적인 비전과 기술 컴포넌트를 정의하고 여러 컴포넌트 사이를 정렬하기 위한 핵심 의사결정을 내릴 수 있어야 합니다. Research outcome을 production-grade 서비스로 발전시키고, 조직의 engineering 및 research standard를 성장시켜 차세대 Tech Lead들을 육성하는 책임도 있습니다.

Responsibilities

  • ● Set the technical vision and roadmap for end-to-end Agentic Search.
  • ● Lead execution from foundational research through production deployment.
  • ● Advance retrieval across sparse/dense/hybrid, reranking, and learning-to-retrieve systems.
  • ● Co-design model-system interfaces spanning search, memory, planning, tool use, and orchestration.
  • ● Develop RL and learning-based methods for search policies, routing, and orchestrator behavior.
  • ● Build rigorous evals for retrieval, grounding, citations, tool use, and long-horizon task completion.
  • ● Optimize quality, latency, throughput, and inference cost across the full search stack.
  • ● Provide technical leadership across Research, Engineering, Infrastructure, and Product.
  • ● Mentor senior technical talent and raise the bar for architecture, research, and execution.
  • ● Deep expertise across the full search stack, beyond dense retrieval.
  • ● Experience building agentic systems, memory systems, or learned orchestrators.
  • ● Applied RL or sequential decision-making to search, agents, or tool use.
  • ● Built end-to-end evaluation systems combining offline evals, online experiments, and production telemetry.
  • ● Scaled ML systems under demanding quality, latency, reliability, and cost constraints.
  • ● Shipped research breakthroughs as reliable, production-grade capabilities.
  • ● Led high-impact technical programs across multiple teams and disciplines.
  • ● A first-principles mindset and strong Staff / Principal-level technical judgment.
  • ● Application Review Coding Test Technical Interview (Online) Culture Fit Interview (Onsite)