AI Researcher (Agentic AI System Architecture)

Responsibilities

• Harness Architecture Design & Implementation
• Research and design Agent execution framework, providing standardized runtime environment for intelligent agents
• Implement tool call orchestration mechanism, supporting unified abstraction for function calling, API integration, and external system interaction
• Build execution sandbox environment to ensure safety and controllability of Agent operations
• Design task decomposition and planning engine, supporting automatic breakdown of complex goals and execution path optimization
• Implement execution state tracking and anomaly recovery mechanisms to ensure reliability of long-running tasks
• Memory System Architecture Development
• Design hierarchical memory architecture, covering storage and retrieval mechanisms for working memory, short-term memory, and long-term memory
• Research memory compression and summarization techniques, enabling efficient storage of massive interaction history while preserving key information
• Build context-aware memory system, supporting multi-dimensional memory association based on time, task, and user
• Develop memory retrieval augmentation mechanisms, achieving deep integration of RAG and Agent memory
• Explore memory forgetting and update strategies, balancing memory capacity with information timeliness
• Multi-Agent Collaboration Architecture
• Research multi-Agent system architecture, design communication protocols and collaboration mechanisms between Agents
• Implement role specialization and task allocation algorithms, supporting orchestration of expert Agents, coordinator Agents, executor Agents, and other roles
• Build consensus achievement and conflict resolution mechanisms to handle decision disagreements among multiple Agents
• Design Agent social behavior norms, simulating communication, negotiation, and feedback patterns in human team collaboration
• Explore emergent behavior and collective intelligence, researching self-organization and adaptive capabilities in multi-Agent systems
• General Architecture Capabilities
• Design Agent evaluation and benchmarking system, establishing quantitative capability metrics
• Build Agent behavior interpretability framework, supporting decision process tracing and attribution analysis
• Research Agent safety alignment mechanisms to prevent risks such as unauthorized operations, harmful outputs, and goal drift
• Track cutting-edge Agentic AI research and translate academic achievements into engineering practice

Requirements

• Basic Qualifications
• Master’s degree or above in Computer Science, Artificial Intelligence, Cognitive Science, or related fields
• 3+ years of AI-related research or development experience, with hands-on experience in Agentic AI and LLM application architecture
• Publishations in top-tier conferences (NeurIPS, ICML, ACL, EMNLP, etc.) are preferred
• Technical Skills
• Programming & Engineering
• Proficient in Python, familiar with asynchronous programming, concurrency control, and performance optimization
• Familiar with mainstream LLM frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, etc.)
• Experience in large-scale distributed system design and implementation
• Familiar with containerization technologies such as Docker and Kubernetes
• AI Expertise
• Deep understanding of Transformer architecture and large model principles
• Familiar with Prompt Engineering, Function Calling, Tool Use, and related technologies
• Experience in RAG system development, familiar with vector retrieval, text Embedding, re-ranking, and related techniques
• Understanding of reinforcement learning fundamentals; experience with RLHF, DPO, and related methods is a plus
• Architecture Design
• Capable of system architecture design, able to independently complete technical solution design for complex modules
• Familiar with design patterns and software engineering best practices
• Good habits in technical documentation writing
• Research Capabilities
• Ability to conduct independent technical research, responsible for the entire process from problem definition to solution implementation
• Strong literature reading and summarization skills, able to quickly absorb cutting-edge research achievements
• Capability in technology selection and evaluation, able to make reasonable decisions among multiple solutions
• Soft Skills
• Strong passion for AI technology, keeping up with the latest developments in the Agentic AI field
• Excellent communication and collaboration skills, able to work efficiently with engineering teams
• Critical thinking ability, capable of objectively evaluating and iteratively optimizing technical solutions
• Preferred Qualifications
• Contributions to Agent framework open-source projects (e.g., LangChain, AutoGen, LlamaIndex)
• Production-level Agent system deployment experience with 10,000+ daily task processing
• Familiarity with cognitive science and human decision-making theory, able to apply them to Agent architecture design
• Research experience in Embodied AI or robotics
• Familiarity with Graph Neural Networks, Knowledge Graphs, and related project experience
• Entrepreneurial experience or experience building AI products from 0 to 1

Benefits

• Medical, dental, and vision insurance
• 401(k) retirement plan with a company match that vests fully on day one
• Paid parental leave after just three (3) months of employment
• Paid time off policy that includes vacation time, personal time, sick time, floating holidays, and company holidays
• Flexible spending and health savings accounts
• Life and AD&D insurance
• Short- and long-term disability coverage
• Legal assistance
• Supplemental plans such as pet, critical illness, accident, and hospital indemnity insurance
• Commuter benefits
• Well-being initiatives
• Peer-to-peer recognition programs