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.