AI Principal Architect

Harness the power of data and artificial intelligence to accelerate change. Come and work with a smart team of data scientists, data engineers, and experts in machine learning and AI. Schneider AI HUB team is a global organization led by the Chief AI officer. AI Hub organization has a mandate to spearhead the AI-driven digital transformation of Schneider Electric.

Artificial intelligence is a confluence of many different technologies working together to enable machines to sense, comprehend, act, and learn with human-like levels of intelligence. Technologies like Machine Learning and Natural Language Processing are all part of the AI landscape. Each one is evolving along its own path and, when applied in combination with data, analytics and automation, can help businesses achieve their goals, be it improving customer service or optimizing the supply chain.

As part of this AI Hub organization, we seek to hire an AI Solution Architect who is passionate about solving complex business & technical problems by applying various AI technologies.

Responsibilities

• Architect, position, design AI solutions which include components across Chatbots, Virtual Assistants, and Machine Learning
• Collaborate with peers across multiple technology disciplines ensuring AI platform and solutions deliver business and technical requirements
• Lead technical workshops in driving strategic initiatives, while developing and managing relationships both internal and external vendors
• Serve program teams to better understand their problems and goals, recommending possible solutions and building consensus around architecture
• Oversee and manage the full AI program life cycle implementations
• Assist, guide, and drive engineering teams by providing technical oversight during implementation and owning technical delivery
• Contribute digital thought leadership with AI-driven mindset to a larger tech community, be a change agent.
• Ensure all architectural consideration and non-functional requirements around high availability, scalability, maintainability, and extensibilities are factored in in the core system.
• Implement POC, sample use case, and core platform components for a highly scalable application.

• Minimum 12 years' experience architecting, designing, developing, and deploying enterprise AI solutions involving Advanced Analytics, Machine Learning and Data Science
• Experience with AI architecture and AI interface design covering diverse range of use cases and deployment models.
• In-depth knowledge of components and architectural trade-offs across data management, governance, model building, and production workflows of AI is a must
• Understand the workflow and planning pipeline architectures of ML and deep learning frameworks, with data, training/retraining and deployment.
• Strong experience practicing Software engineering and DevSecOps principles, including knowledge of CI/CD workflows and tools (exposure to MLOps/MLFlow)
• Demonstrated expertise in modeling techniques with types of algorithms and development at least one of the following machine learning, deep learning, time-series, anomaly detection and prediction
• In-depth theoretical and practical knowledge in few select areas across AI cloud spectrum AWS AI/ML Services, MS Azure ML Services and Databricks
• Knowledge and ability to apply OOPS concepts, SOLID principles, and design patterns.
• Experience with Computer Science fundamentals in data structures, algorithms, and complexity analysis
• Hands on programming skills especially in Python.
• Good Analytical skills.
• Good knowledge of Generative AI & Agentic AI.