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JobsSchneider Electric

AI Product Owner

Schneider Electric

AI Product Owner

Schneider Electric

上海, 中国; 北京, 中国

·

On-site

·

Full-time

·

6d ago

The AI Product Owner is a core key role in AI projects within a global organization.

Focused on the in-depth integration of AI technology and internal business scenarios, this role delivers core value to the internal functional teams while maintaining a clear grasp of internal team needs and the key goals of AI project implementation.

Acting as a critical bridge between internal functional teams and the AI development team (algorithm & LLM engineers, frontend engineers, data scientists), the role requires a solid basic understanding of AI and architecture sorting capabilities to translate the needs and ideas of internal teams into technical language and implementation paths that the AI development team can understand and execute.

Additionally, the role represents the demands of internal functional teams, communicates a clear product vision within the AI development team, builds and maintains close collaborative relationships with internal stakeholders (functional teams, technical teams, sponsors, etc.).

Collaborating with internal AI Champions to set project priorities, define, own, and maintain the AI project backlog, drive the strategic implementation of AI projects, and maximize project value output.

Through effective leadership, establish a collaborative and win-win cross-functional team environment, and take responsibility for the entire lifecycle of AI projects—from requirement definition, technical selection, model iteration, and internal deployment to effect tracking—ensuring the achievement of project results and the realization of internal business value.

Your missions : 1. AI Project Value Proposition & Strategy Formulation Align with AI Champions to define the core value proposition and strategy of AI projects, ensure the team achieve strategic goals.

Dive deep into internal business scenarios, communicate extensively with internal functional teams and stakeholders to identify pain points and efficiency improvement opportunities driven by AI.

Understand internal team business logic, AI application scenarios, internal workflow requirements, and business process evolutions.

Lead and participate in the formulation of internal team collaboration strategies to ensure the AI product direction aligns with actual internal business needs.

Track cutting-edge AI technology trends to identify high-value AI innovations and application scenarios in internal business processes. 2. AI Project Management, Deployment & Support Collaborate with internal functional teams to build, follow up on, and support the entire internal deployment and application process of AI projects.

Analyze and co-build AI projects business cases with internal teams, focusing on core values brought by AI technology such as internal workflow optimization, efficiency improvement, and cost reductions.

Collect and analyze internal team needs through regular meetings, workflow interviews and cross-team collaborations, and translate them into implementable AI product requirements.

Conduct periodic analysis of AI project internal application performance, including model application effects, business indicator achievement rates (such as accuracy, internal adoption rate), process efficiency improvements, and iterative evolution trends.

Provide support to internal functional teams, including requirement reviews, AI tool usage training, etc.

Coordinate the internal launch and promotion activities of AI projects, collaborate with various internal teams to complete deployment and application. 3. AI Project Roadmap Management Create, prioritize and communicate the AI project roadmap to stakeholders.

Develop the AI project release plan and roadmap based on technology feasibility, computing power budget, internal resource allocation, data cycle, and other factors.

Regularly align project progress with internal stakeholders and collect feedback from internal teams on AI Project prototypes/demos, iteratively optimize requirements and roadmaps. 4.

Cross-Functional Team Leadership Establish a collaborative environment conducive to AI project advancement through effective leadership.

Provide transparency on AI project progress, risks, and achievements to core internal stakeholders, ensuring timely and accurate information synchronization.

Recognize and celebrate key achievements and milestone breakthroughs of the team in AI projects to enhance team cohesion. 资格 Master's degree in artificial intelligence, computer science, software engineering, Electrical Engineering or related fields. 4+ years of product development experience, or 3 years of experience in project development on an Agile Team with proven results.

Solid basic understanding of AI, familiar with AI technology stack (such as machine learning, deep learning, large language models (LLMs), Agentic AI), data processing processes, and the AI project architecture and technical implementation paths.

Experience: in the entire lifecycle management of AI projects, responsible for project results, with practical capabilities in tracking internal deployment effects and iterative optimization.

Experience: in successfully building and leading cross-functional teams in a matrix organization.

Excellent communication, facilitation, negotiaion, and coaching skills, capable of effectively connecting internal functional teams and technical teams.

Strong results-oriented and problem-solving abilities, proficient in formulating project plans based on AI technology characteristics and internal business goals, 时间表: 全职 请求编号: 009JL2

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About Schneider Electric

Schneider Electric

Schneider Electric SE is a French multinational corporation that specializes in energy technology, covering electrification, automation, and digitalization for industry and homes.

10,001+

Employees

Rueil-Malmaison

Headquarters

Reviews

4.0

45 reviews

Work Life Balance

3.6

Compensation

4.3

Culture

4.2

Career

4.5

Management

3.5

84%

Recommend to a Friend

Pros

Cutting-edge technology stack and interesting technical challenges

Competitive compensation packages with equity

Strong engineering culture with focus on code quality

Cons

Some legacy systems that need modernization

Work-life balance can be challenging during product launches

Fast-paced environment with tight deadlines

Salary Ranges

3 data points

Principal/L7

Senior/L5

Principal/L7 · Principal Data Scientist

0 reports

$211,000

total / year

Base

-

Stock

-

Bonus

-

$179,350

$242,650

Interview Experience

3 interviews

Difficulty

2.7

/ 5

Duration

14-28 weeks

Offer Rate

33%

Experience

Positive 33%

Neutral 67%

Negative 0%

Interview Process

1

Application Review

2

Technical/Hiring Manager Interview

3

HR Screen

4

Final Interview Round

5

Offer

Common Questions

Technical Knowledge

Behavioral/STAR

Past Experience

Culture Fit