GenAI Architect

Experience Level: Minimum 12+ years

Must Have Key Responsibilities:

• Collaborate with data scientists, engineers, and product managers to identify AI opportunities and define project requirements.
• Evaluate and select appropriate AI technologies, tools, and platforms to optimize performance and scalability.
• Lead the development of AI algorithms and models, ensuring they are robust, efficient, and aligned with best practices.
• Conduct research on emerging AI trends and technologies to inform strategic decisions and maintain a competitive edge.
• Oversee the integration of AI solutions into existing systems and workflows, ensuring seamless functionality.
• Provide technical guidance and mentorship to team members on AI-related projects and initiatives.
• Monitor and evaluate the performance of AI models, making necessary adjustments to improve accuracy and efficiency.
• Communicate complex AI concepts and solutions to non-technical stakeholders in a clear and concise manner.
• Develop a deep understanding of Azure solution architecture, including infrastructure, services, cost management, and monitoring.

Qualifications:

• Proven experience as an AI Architect or in a similar role, with a strong portfolio of successful AI projects.
• Experience with cloud platforms (e.g., Azure, Google Cloud, AWS) and big data technologies, specifically Azure Data Lake, Databricks, and other big data processing tools (e.g., Hadoop, Spark).
• Basic Understanding of machine learning algorithms, deep learning, natural language processing, and computer vision.
• Understanding of cloud infrastructure, services, cost management, and monitoring.
• Knowledge of AI tools and GenAI and Agentic AI frameworks.
• Exposure to cloud architecture principles and practices, with a focus on improvement.
• Ability to learn quickly and adapt to new technologies and methodologies.
• Experience in deploying AI solutions in production environments.
• Knowledge of data engineering and data management best practices.

Preferred Skills:

• Experience with other cloud platforms such as Google Cloud and Amazon Web Services.
• Understanding of system design principles and cloud deployment strategies.