该职位来源于猎聘 Summary: We are seeking a highly skilled and self-driven AI Architect to lead the development and implementation of our core AI infrastructure and smart factory solutions. As an AI expert, you will own the design, deployment, and maintenance of the Dify low-code AI platform and custom RAG system, while architecting AI-driven solutions to optimize industrial operations. This role requires a blend of technical depth, industrial domain awareness, and cross-functional collaboration to translate AI capabilities into tangible business value. Key Responsibilities:
Dify System Development & Management
Lead the full lifecycle of the Dify system: conduct business requirement analysis (with production/IT teams), deploy the Dify platform, customize core functions (e.g., develop plugins for industrial data integration, building custom AI workflows), manage user permissions, and ensure 99.9%+ system stability.
Troubleshoot Dify-related issues and iterate on the system to support evolving needs (e.g., integrating with factory MES/ERP software).
RAG Platform Design & Implementation
Build a production-grade RAG platform tailored for industrial scenarios: select and deploy vector databases, design hybrid retrieval strategies, process industrial unstructured data (e.g., OCR for equipment manuals, text chunking for production logs), and integrate LLMs to enable use cases like real-time maintenance knowledge queries and production process guidance.
Optimize RAG performance through continuous testing and algorithm adjustments.
Smart Factory AI Architecture & Delivery
Architect AI solutions for smart factory scenarios: define technical roadmaps, select appropriate AI models/tools and design scalable data pipelines (integrating IoT device data via MQTT protocols).
Lead end-to-end implementation: collaborate with production teams to collect/clean industrial data, train/validate AI models, deploy solutions, and monitor model performance in real time.
Provide technical support for AI-enabled factory operations: train on-site teams to use AI tools, document solution architectures, and resolve post-deployment issues.
AI Technology Leadership & Innovation
Stay ahead of AI/industrial tech trends (e.g., LLM fine-tuning for manufacturing, edge AI for real-time data processing) and propose innovative use cases to drive business impact.
Act as the internal AI expert: conduct knowledge sharing sessions, advise cross-functional teams on AI feasibility, and ensure AI solutions comply with data security and privacy standards. Required Hard Skills
Dify Platform Expertise
Proven experience deploying, customizing, and maintaining the Dify system (e.g., building custom plugins, configuring AI agents, integrating external APIs/data sources).
Familiarity with Dify's backend architecture and frontend customization is a plus.
RAG & LLM Technical Proficiency
Deep understanding of RAG principles: experience with vector databases, retrieval algorithms, and document processing (OCR, text embedding, chunking strategies).
Hands-on experience with LLMs: fine-tuning, model integration, and prompt engineering for technical/industrial use cases.
Programming & Software Development
5+ years Python, Java, SQL. Have experience in PyTorch, Hugging Face, MLOps tools (Kubeflow, Docker). Also familiar with API development, and scripting for automation.
proficiency in data processing, Familiarity with frontend basics (JavaScript/HTML/CSS) for Dify UI tweaks; experience with version control (Git) and CI/CD pipelines for AI system deployment.
Industrial AI & IoT Knowledge
Understanding of smart factory workflows (e.g., production scheduling, equipment maintenance, quality control) and ability to map AI solutions to these processes.
Experience with industrial data protocols MQTT for integrating IoT devices and industrial software.
Knowledge of industrial AI use cases: building predictive maintenance models, computer vision for defect detection, or optimization models for production efficiency.
System Architecture & Deployment
Ability to design scalable AI architectures: experience with distributed systems, microservices, and cloud/edge deployment. Proficiency in containerization and orchestration for deploying AI models/RAG platforms in production.
Familiarity with monitoring tools to track AI system performance and data drift.
Database & Data Security
Experience with relational databases for structured industrial data and NoSQL databases for unstructured data.
Knowledge of data security best practices (e.g., data encryption, access control) and compliance with industrial data regulations.
Big data processing (Spark, Kafka), IoT data integration Required Soft Skills
Independent Problem-Solving
Ability to work autonomously to define project scopes, troubleshoot technical issues, and deliver solutions.
Proactive approach to identifying gaps and proposing actionable fixes.
Cross-Functional Collaboration
Strong communication skills to translate technical AI concepts into non-technical language for production, IT, and leadership teams.
Experience collaborating with non-technical stakeholders to gather requirements and align AI solutions with business goals.
Adaptability & Learning Agility
Fast learner who can quickly master new AI tools and adapt to evolving business needs.
Proactive in staying updated on AI/industrial trends and applying new knowledge to projects.
Accountability
Takes full ownership of AI systems and projects: responsible for post-deployment maintenance, performance monitoring, and continuous improvement.
Preferred Qualifications
2+ years of experience implementing AI solutions in manufacturing/smart factory environments.
Previous experience building or maintaining Dify or similar low-code AI platforms.
Hands-on RAG project experience.
Experience with edge AI deployment (e.g., running models on edge devices for real-time industrial data processing).
Certifications in AI/ML, e.g., AWS Certified Machine Learning and NVIDIA-Certified Associate.