Senior Principal, Solution Architect
Schneider Electric
Bengaluru, Karnataka, India
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 Qualifications Requirements and Skills 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 algorithm 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 and MS Azure ML Services Knowledge and ability to apply OOPS concepts, SOLID principles, and design patterns. Experience with Computer Science fundamentals in data structures, algorithms, and complexity analysis Good Analytical skills.