Associate Director - AI Architecture

As an Associate Director in this role, you will be responsible for developing the overarching technical vision for AI systems that support current and future business needs. Your key responsibilities will include: - Architecting end-to-end AI applications, ensuring integration with legacy systems, enterprise data platforms, and microservices. - Working closely with business analysts and domain experts to translate business objectives into technical requirements and AI-driven solutions and applications. - Leading the design of reference architectures, roadmaps, and best practices for AI applications. - Evaluating emerging technologies and methodologies, recommending proven innovations for integration into the organizational strategy. - Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems. - Utilizing containerization and cloud services for deployment and scaling of AI systems. - Ensuring architecture supports scalability, reliability, maintainability, and security best practices. - Overseeing project planning, execution, and delivery of AI and ML applications within budget and timeline constraints. - Enforcing security best practices during each phase of development. - Providing mentorship to engineering teams and facilitating continuous learning. - Leading technical knowledge-sharing sessions to keep teams updated on the latest advances in generative AI and architectural best practices. Qualifications required for this role include: - Bachelors/Masters degree in Computer Science. - Certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification (good to have). - 11 to 14 years of work experience. Mandatory technical and functional skills for the ideal candidate include: - Strong background in developing agents using langgraph, autogen, and CrewAI. - Proficiency in Python and knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras. - Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) and containerization (Docker) and orchestration frameworks (Kubernetes). - Proficient in SQL and NoSQL databases and designing distributed systems, RESTful APIs, and microservices architecture. - Knowledge of event-driven architectures and message brokers. Preferred technical and functional skills include: - Experience with monitoring and logging tools and familiarity with cutting-edge libraries and domain-specific tools. - Large scale deployment of ML projects and training and fine-tuning of Large Language Models. Key behavioral attributes/requirements for this role: - Ability to mentor junior developers. - Ability to own project deliverables and contribute towards risk mitigation. - Understanding of business objectives and functions to support data needs. As an Associate Director in this role, you will be responsible for developing the overarching technical vision for AI systems that support current and future business needs. Your key responsibilities will include: - Architecting end-to-end AI applications, ensuring integration with legacy systems, enterprise data platforms, and microservices. - Working closely with business analysts and domain experts to translate business objectives into technical requirements and AI-driven solutions and applications. - Leading the design of reference architectures, roadmaps, and best practices for AI applications. - Evaluating emerging technologies and methodologies, recommending proven innovations for integration into the organizational strategy. - Identifying and defining system components such as data ingestion pipelines, model training environments, CI/CD frameworks, and monitoring systems. - Utilizing containerization and cloud services for deployment and scaling of AI systems. - Ensuring architecture supports scalability, reliability, maintainability, and security best practices. - Overseeing project planning, execution, and delivery of AI and ML applications within budget and timeline constraints. - Enforcing security best practices during each phase of development. - Providing mentorship to engineering teams and facilitating continuous learning. - Leading technical knowledge-sharing sessions to keep teams updated on the latest advances in generative AI and architectural best practices. Qualifications required for this role include: - Bachelors/Masters degree in Computer Science. - Certifications in Cloud technologies (AWS, Azure, GCP) and TOGAF certification (good to have). - 11 to 14 years of work experience. Mandatory technical and functional skills for the ideal candidate include: - Strong background in developing agents using langgraph, autogen, and CrewAI. - Proficiency in Python and knowledge of machine learning libraries such as TensorFlow, PyTorch, and Keras. - Experience with cloud computing platforms (AWS, Azure, Google Cloud Platform) and containerization (Docker) and orchestration frameworks (Kubernet