R&D Engineer – Manufacturing Digital Employee Platform

Job Responsibilities Innovation & Research:

• Explore state-of-the-art technologies in enterprise AI agents, retrieval-augmented generation, multimodal document understanding, workflow automation, tool calling, and manufacturing system integration.
  • Lead the design and development of core modules for the AIKnoworks Manufacturing Digital Employee Platform, including manufacturing knowledge understanding, trusted Q&A, agent task execution, workflow orchestration, and cross-system connectivity.
  • Research and implement key capabilities such as document parsing, semantic chunking, hybrid retrieval, source tracing, task planning, tool selection, state tracking, exception handling, and human-in-the-loop collaboration.
  • Design enterprise-grade mechanisms for permission control, task auditing, operation logging, result verification, error rollback, and risk alerts to ensure controllability, reliability, and traceability in manufacturing scenarios.
  • Participate in platform architecture design, including API integration, local deployment, model serving, high-concurrency task scheduling, data security, version management, and system upgrade strategies.

Collaboration & Implementation:

• Collaborate with manufacturing clients and internal product teams to identify common industry needs and translate them into reusable platform capabilities rather than one-off customized solutions.
  • Develop and validate connector architectures for ERP, MES, PLM, QMS, WMS, OA, CRM, email systems, databases, document systems, and other enterprise platforms.
  • Participate in system integration, testing, performance evaluation, and productization, continuously improving task success rate, answer accuracy, tool-calling stability, and workflow execution efficiency.
  • Analyze testing data, error cases, and human feedback to optimize retrieval strategies, agent planning logic, model invocation methods, and platform safety mechanisms.
  • Contribute to building a scalable, reusable, and industry-level digital employee technology architecture for manufacturing enterprises.

Qualifications & Preferred Skills Education & Foundation:

• Master’s or PhD in Computer Science, Artificial Intelligence, Software Engineering, Industrial Engineering, Automation, or a related field.
  • Solid foundation in algorithms, machine learning, system architecture, and software engineering, with strong interest in enterprise AI and intelligent manufacturing.

Technical Expertise:

• Proficiency in Python, Java, C++, or other mainstream programming languages, with hands-on experience in system development and algorithm implementation.
  • Familiarity with large language models, RAG, knowledge bases, vector databases, workflow engines, agent frameworks, or tool-calling systems.
  • Experience with document parsing, multimodal understanding, API integration, database systems, or enterprise application integration is a plus.
  • Familiarity with Linux, Git, Docker, RESTful APIs, model deployment, and local/private deployment environments preferred.
  • Knowledge of manufacturing systems such as ERP, MES, PLM, QMS, WMS, or related industrial software is a strong advantage.

Mindset & Competencies:

• Passionate about applying AI technologies to real-world manufacturing and enterprise productivity challenges.
  • Strong research, problem-solving, and engineering implementation capabilities, able to transform technical concepts into deployable platform features.
  • Strong sense of productization, reliability, security, and scalability in enterprise software development.
  • Excellent communication and cross-functional collaboration skills, capable of working effectively across Hong Kong, Mainland China, or remote teams.