AI Architecture

Role Overview: As an AI Architect in our team, you will be responsible for defining the overall AI strategy, identifying potential use cases, and business opportunities for AI implementation across various departments. Your role will involve developing and documenting the technical architecture for AI systems, selecting appropriate AI tools and platforms, overseeing data management for AI model training, designing and optimizing AI models, integrating them into existing systems, monitoring performance, and ensuring ethical considerations are met. Key Responsibilities: - Strategic planning: Define the overall AI strategy and identify potential use cases and business opportunities for AI implementation. - Architecture design: Develop and document the technical architecture for AI systems, including data pipelines, model selection, training infrastructure, and deployment environments. - Technology selection: Evaluate and choose appropriate AI tools, frameworks, and platforms based on project requirements and organizational needs. - Data management: Oversee data collection, cleaning, labeling, and preparation for AI model training to ensure data quality and governance. - Model development: Collaborate with data scientists and machine learning engineers to design, train, and optimize AI models, including deep learning algorithms. - Integration and deployment: Integrate AI models into existing systems and applications, ensuring seamless functionality and scalability. - Performance monitoring: Monitor AI model performance in real-world scenarios, identify issues, and implement necessary adjustments. - Ethical considerations: Adhere to ethical guidelines related to data privacy, bias detection, and responsible AI development. Qualification Required: - Bachelor's degree in Computer Science, Engineering, or a related field. - 5+ years of proven experience in big data, analytics, and data science. - Previous experience as an AI engineer will be a good-to-have. - Certification in Google Cloud AI platform, Azure AI engineer, or similar AI tools will be an added skill. - Deep understanding of machine learning algorithms, statistical analysis, natural language processing, computer vision, and related AI technologies. - Expertise in programming languages like Python, Java, and experience with cloud computing platforms like AWS, Azure, or GCP. - Strong data analysis skills including data cleaning, feature engineering, and model evaluation. - Ability to design and implement complex distributed systems considering scalability and performance optimization. - Understanding of business needs and ability to translate them into actionable AI solutions. - Effective communication with both technical and non-technical stakeholders to explain complex AI concepts.,