AI Architect

Unisys — Bangalore, KA, India

What success looks like in this role: The key responsibilities of an Architect position can vary depending on the specific industry, organization, and project requirements. However, some common responsibilities typically associated with an Architect role include: 1. Architecting Data Solutions : Designing and architecting end-to-end data science solutions that meet business objectives. This involves understanding the business requirements, data infrastructure, and available technologies to create scalable and efficient data architectures. Agentic AI, AI Agent, Azure Foundry, AWS, Cloud 2. Data Modeling and Analysis : Developing data models and algorithms to analyze complex datasets, extract insights, and make data-driven decisions. This may involve machine learning, statistical analysis, and data mining techniques. 3. Technical Leadership : Providing technical leadership to the data science team, guiding them in best practices, methodologies, and tools for data analysis and modeling. Mentoring junior team members and fostering a culture of collaboration and innovation. 4. Infrastructure Design and Optimization : Designing and optimizing data infrastructure, including databases, data warehouses, and data lakes, to support large-scale data processing and analytics. This may involve selecting appropriate technologies, optimizing data pipelines, and ensuring scalability and reliability. 5. Integration and Deployment : Integrating data science solutions with existing systems and applications, and overseeing the deployment and implementation process. This may involve working closely with software engineers, IT professionals, and other stakeholders to ensure smooth integration and deployment. 6. Data Governance and Compliance : Establishing data governance policies, standards, and procedures to ensure data quality, privacy, and security. Ensuring compliance with regulatory requirements such as GDPR, HIPAA, or industry-specific regulations. 7. Performance Monitoring and Opt

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