Job Description

At Schneider Electric, we are committed to solving real-world problems to create a sustainable, digitized, new electric future. Artificial Intelligence has the potential to transform industries and help unlock efficiency and sustainability.

Within our Global AI Hub we combine our long-standing manufacturing and domain expertise with cutting-edge innovation in AI, machine learning, and deep learning to empower smarter decision-making, agility, and decarbonization.

The AI Offers team is looking for a top-notch Technical Product Manager to drive the strategy and implementation of Conversational AI use-cases by solving customer challenges and building delightful experiences. You will collaborate with stakeholders in Business Functions, Engineering teams and Executives to build a comprehensive roadmap and deliver on it.

Your missions : 

• Own the ‘What’ and the ‘Why’ -
• Partner with Business and Product leadership to define and drive the Conversational AI products’ strategy and direction for Global Functions. Start with the end-users to understand the pain-points and work backwards including the vision, long-term roadmap, success metrics and key milestones with data driven decisions.
• Keep a tab on the Conversational AI trends and advancements in the market and have a thorough understanding of the use-case that can be addressed by applying these technologies.
• Work with stakeholder across all levels to assess, initiate, prioritize and refine the product backlog including high quality user-stories with detailed Acceptance criteria that represents the requirements.

• Influence the ‘How’ – Be able to lead without authority and Collaborate with the AI Engineering and multiple teams across Schneider to deliver the products and features as committed on time and with high-quality.
• Be Obsessed about the end user experience offered by the products - Closely work with experienced UX designers to understand the user needs and behavior by participating in design thinking sessions, ensuring that user goals and scenarios are well understood, tested, and translated into fantastic designs and conversational flows.
• Have a good understand of the Tech stack - Architecture, features, capabilities, and limitations. Participate in the technical discussions with Engineering leaders and Architects to influence the Technical platform roadmap based on the use-case backlog. Be able to resolve complex technical trade-offs with a clear understanding of the Business impact and technical implementation choices.
• Collaborate with Engineering to evolve the Conversational AI Framework in Schneider Electric with the goal to develop Virtual assistants @speed and scale, and to deliver intuitive, consistent & personalized experience for the end-users.
• Drive innovation to improve Usability, NPS and CSAT.

• Be an evangelist for communicating product benefits to the Leaders and interested community and drive the adoption of the Virtual Assistants across SE employees, partners, and customers.

• Always obsessed about delivering Value through these Chatbot initiatives and be accountable to ensure the realization of value for the built products.                                                  

Your profile : 

• 10+ years of total experience; 4+ years of s/w development experience working as a developer/Engineer in the beginning of your career, and 5+ years of Technical Product/Program management, and minimum of 2+ years of building Enterprise grade chatbots as a TPM
• Strong track record of delivering Chatbots and other Conversational AI use-case in support, sales, HR, Enterprise IT, or other functions.
• Experience in driving the ‘What’ and ‘Why’ and technical depth to influence the ‘How’ across globally matrixed team and making critical trade-offs, while developing and executing the product roadmap for Chatbots in an Enterprise.
• Experience of using Azure AI/ MSBF, AWS Lex, Dialogflow, or another Chatbot framework to build chatbots for simple to complex Enterprise use-cases.
• Experience with or a sound understanding of building machine learning models for Natural language understanding, and conceptual understanding of LLMs.
• Experience of working on Agile development teams. Knowledge of professional software engineering practices for s/w development lifecycle.
• Track record of problem-solving using MVPs, pilots and other growth hacking approaches.