AI Architect

• Design and define the overall architecture for AI, Machine Learning, and Generative AI solutions across the organization.
• Translate business requirements into scalable AI/ML solutions and technical architectures.
• Lead the design and development of end-to-end AI systems including data pipelines, model development, and deployment.
• Select appropriate AI frameworks, tools, and cloud platforms for building robust AI solutions.
• Collaborate with data scientists, data engineers, and application developers to implement AI-driven applications.
• Establish best practices for AI development, model governance, security, and scalability.
• Guide teams on MLOps practices including model training, versioning, monitoring, and lifecycle management.
• Integrate AI solutions with existing enterprise systems, APIs, and business applications.
• Evaluate and adopt emerging technologies such as Generative AI, LLMs, and advanced analytics tools.
• Provide technical leadership, mentorship, and architectural guidance to AI and engineering teams.
• Ensure AI solutions meet performance, reliability, and compliance standards.
• Drive innovation by identifying opportunities to leverage AI for business process improvement and decision-making.
• Work closely with stakeholders to align AI strategies with business goals and digital transformation initiatives

Job Type: Full Time

Job Location: Bhopal

Experience: 7-12 years

• Design and define the overall architecture for AI, Machine Learning, and Generative AI solutions across the organization.
• Translate business requirements into scalable AI/ML solutions and technical architectures.
• Lead the design and development of end-to-end AI systems including data pipelines, model development, and deployment.
• Select appropriate AI frameworks, tools, and cloud platforms for building robust AI solutions.
• Collaborate with data scientists, data engineers, and application developers to implement AI-driven applications.
• Establish best practices for AI development, model governance, security, and scalability.
• Guide teams on MLOps practices including model training, versioning, monitoring, and lifecycle management.
• Integrate AI solutions with existing enterprise systems, APIs, and business applications.
• Evaluate and adopt emerging technologies such as Generative AI, LLMs, and advanced analytics tools.
• Provide technical leadership, mentorship, and architectural guidance to AI and engineering teams.
• Ensure AI solutions meet performance, reliability, and compliance standards.
• Drive innovation by identifying opportunities to leverage AI for business process improvement and decision-making.
• Work closely with stakeholders to align AI strategies with business goals and digital transformation initiatives