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.
ResponsibilitiesCore 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 RequirementsBasic 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 SkillsProgramming & 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
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