# Superintelligence Lab - Tech Lead (Agentic Search, Staff / Principal Level) at LG AI Research

> South Korea · Principal · Other · open. Source: https://alderhq.app/jobs/greenhouse%3Algairesearch%3A4080978005 (read 2026-11-13).

## Facts (observed)

- Company: [LG AI Research](https://alderhq.app/companies/lg-ai-research)
- Location text: Gangseo-gu, Seoul, South Korea; LG AI Research Magok
- Where it can be done from (inferred): South Korea (evidence: "Location: Gangseo-gu, Seoul, South Korea; LG AI Research Magok")
- Posted: 2022-08-23 (1543 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://www.lgresearch.ai/careers?gh_jid=4080978005

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### 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.

### What You’ll Do

- 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.
### You Might Thrive in This Role If You Have

- 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.
### 전형 절차

- Application Review → Coding Test → Technical Interview (Online) → Culture Fit Interview (Onsite)
\* 전형 절차는 변경될 수 있습니다. 서류 합격 시 전형 절차에 대해 별도로 안내 해 드립니다.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Algairesearch%3A4080978005 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.