Description
Roles & responsibilities
Here are some of the key responsibilities of AI architect:
1.Develop the overarching technical vision for AI systems that support both current and future business needs.
2.Architect end-to-end AI applications, ensuring integration with legacy systems, enterprise data platforms, and microservices.
3.Work closely with business analysts and domain experts to translate business objectives into technical requirements and AI-driven solutions and applications. Partner with product management to design agile project roadmaps, aligning technical strategy with market needs. Coordinate with data engineering teams to ensure smooth data flows, quality, and governance across data sources.
4.Lead the design of reference architectures, roadmaps, and best practices for AI applications.
5.Evaluate emerging technologies and methodologies, recommending proven innovations that can be integrated into the organizational strategy.
6.Identify and define system components such as data ingestion pipelines, model training environments,
continuous integration/continuous deployment (CI/CD) frameworks, and monitoring systems.
7.Utilize containerization (Docker, Kubernetes) and cloud services to streamline the deployment and scaling of AI systems. Implement robust versioning, rollback, and monitoring mechanisms that ensure system stability, reliability, and performance.
8.Ensure the architecture supports scalability, reliability, maintainability, and security best practices.
9.Project Management: You will oversee the planning, execution, and delivery of AI and ML applications, ensuring that they are completed within budget and timeline constraints. This includes project management defining project goals, allocating resources, and managing risks.
10.Oversee the lifecycle of AI application development—from conceptualization and design to development, testing, deployment, and post-PROD optimization.
11.Enforce security best practices during each phase
📌 Associate Director (Bengaluru)
🏢 BSR
📍 Bengaluru