BPS & AI engineer_PS

Wuxi, Jiangsu, cn on site Until 8/22/2026 H-1B sponsor history First posted May 14, 2026 Last posted May 14, 2026
Job description

Bosch Powertrain Systems Co., Ltd. (RBCD), the joint venture of Robert Bosch GmbH and Weifu High Technology Group Co., Ltd., is a high tech enterprise specializing in the development, production and sales of common rail systems, exhaust gas after treatment systems, fuel cell stacks and key components. The company, based on its local R&D and project management competence, with innovative technologies, can support customers to continuously improve internal combustion engines efficiency, to reduce emission, and to accelerate the market launch of new energy products. The garget of the company is to provide the Chinese market and customers with diversified advanced powertrain products.

Act as a key bridge between the production area and digital/AI developers.
Responsible for collecting and clarifying business needs from MOE and driving the practical application and rollout of BPS and Artificial Intelligence (AI) solutions.
Support the Value Streams in their daily operations by facilitating continuous improvement (CIP) and empowering associates with user-friendly digital and AI tools
AI Implementation:
• Needs Analysis: Work closely with the Value Stream (VS) and production teams to collect, clarify, and translate operational pain points into actionable digital or AI use cases.
• Application & Rollout: Support the implementation and daily AI & digital applications (e.g., AI associates, AI for quality improvement ect).
• Tool Utilization: Assist local teams in using GenAI tools, low-code platforms (e.g., Dify), and Text-to-SQL applications to improve efficiency in daily tasks like document processing, problem analysis, and basic data extraction

BPS implementation & Continuous Improvement (CIP)
• Support Value Stream members in applying the BPS system approach (tact, flow, and rhythm) in their daily work.
• Facilitate fast improvement activities (e.g., Speed week / BLI) in the production area, helping teams use digital dashboards and tools to visualize Throughput Time (TPT) and eliminate waste.
• Support the integration of traditional BPS methods (like value stream mapping and systematic CIP) with shopfloor digital tracking tools

Training & Empowerment
• Competence Building: Provide user-level training on BPS basics, problem-solving methods, and the application of new digital/AI tools
• Digital Culture: Support initiatives like the Shopfloor EDT (Empowered Digital Team) Learning Camp to build a culture of active learning and digital transformation among production associates

• Education: Master's degree in AI, computer science, Information Technology or a related field.
• Professional Experience: Practical experience in production, lean manufacturing (BPS)
• Digital/AI Literacy: Familiarity with the concepts of digitalization, Industry 4.0, and GenAI applications. Coding skills (like basic Python or SQL) are a plus, but the primary requirement is a strong interest and ability to quickly learn and apply digital tools in a business context.
• General Skills: Good English and computer skills. Strong analytical and problem-solving mindset.
• Communication & Bridging: Excellent interpersonal and requirement-gathering skills. Ability to communicate effectively with both production colleagues and technical IT/AI developers. Able to lead and influence without direct authority

About this role

Summary

Facilitate digital and AI solutions, support continuous improvement, and bridge production with AI teams.

Job title

BPS & AI engineer_PS

Experience level

practical experience in production, lean manufacturing (BPS)

Industry

automotive

Location requirements

Wuxi, Jiangsu; remote work not specified

Salary

Not specified

Visa sponsorship

H-1B sponsor history

Management role

No

Skills & keywords

Required skills

master's degreeAIcomputer scienceITPythonSQLEnglishanalytical

Preferred skills

None specified

Specializations

AIdigitalizationIndustry 4.0genailow-code
Locations

Structured locations inferred from the posting.

Wuxi, Jiangsu, China

On-site City