AI Researcher (Agentic AI System Architecture)
Genscript · Piscataway, New Jersey, United States · Posted Jun 24, 2026
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About GenScript
Founded in 2002 in New Jersey, GenScript Biotech Corporation accelerates innovation in biotech and healthcare by providing researchers and companies with the building blocks needed to develop groundbreaking treatments and products. Guided by its mission to Make People and Nature Healthier Through Biotechnology, and its role as a well-recognized biotechnology company, GenScript has a team of approximately 6,165 employees and has served more than 200,000 customers across over 100 countries and regions.
Job Title: AI Researcher (Agentic AI System Architecture)
Location : Piscataway, NJ
The estimated salary range for this role is $85,000 - $145,000 depending on experience.
Responsibilities
Core Research Directions, responsible for one or two of the following areas:
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
Job 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
Publications 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 evaluat…