Binance

Overview

Design and operate next-generation retrieval pipelines and frontier harness for agentic AI systems in production.

About Binance

Binance is a leading global blockchain ecosystem behind the world’s largest cryptocurrency exchange by trading volume and registered users.

Requirements & Eligibility

• 2-8+ Year hands-on experience with LLM, RAG and AI agent systems in production
• Hands-on experience building production retrieval pipelines end-to-end — embedding models, vector stores, hybrid search, reranking models
• Hands-on experience with Agent Harness runtimes
• Deep familiarity with LLM and agent mechanisms — LLM APIs, KV Cache, Agent Loop, Tool Use, Reasoning, Planning, Skills, MCP, Memory, Subagent, Multi-Agent
• Independent Research Capability: Can analyze ambiguous problems from first principles, generate original ideas, and drive research from 0 to 1
• Heavy Agent User: Power user of agent products
• Proficient in vibe coding — ships fast using AI-assisted workflows

Key Responsibilities

• Design and operate next-generation retrieval pipelines — moving beyond static retrieve-once patterns to adaptive, self-correcting, and multi-hop retrieval workflows; architect Agentic RAG systems with dynamic retrieval control, query decomposition, i
• Collaborate deeply with researchers and engineers to define and implement model-capability-driven innovations — including context management, long-term memory, subagent and multi-agent architectures, self-evolving agents, and real-word task execution
• Propose harness-domain and RAG-domain benchmarks and evaluation methodologies; construct benchmark datasets, define annotation strategies, and systematically measure and improve agent intelligence across domains
• Leverage multi-channel user feedback and real-world task data as primary research signals; design experiments and datasets to continuously improve agent and retrieval performance in production scenarios