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About the role
Key Responsibilities - Lead the end-to-end design, development, and deployment of Generative AI agents using Google ADK, LangGraph, and Crew.AI frameworks. - Architect scalable AI solutions within the Google Cloud Platform (GCP) ecosystem, leveraging Gemini Enterprise and the Gemini Agent Platform. - Manage and mentor a high-performing team of AI engineers to ensure the delivery of cutting-edge industrial AI solutions. - Collaborate with cross-functional teams to integrate generative AI models into sovereign cloud environments and industrial operations (such as energy, utilities, and manufacturing). - Drive the creation of robust Python-based AI pipelines for multi-cloud orchestration and real-time edge computing. - Establish best practices for AI model evaluation, prompt engineering, and agentic framework deployments across the organization. - Oversee the lifecycle of AI products from conceptualization to production, ensuring alignment with Adani AI Labs's strategic capabilities. - Troubleshoot complex AI/ML system bottlenecks and optimize model inference performance on GCP to enhance operational efficiency. Domain Expertise - Deep understanding of Generative AI, Large Language Models (LLMs), and complex agentic workflows. - Familiarity with industrial AI applications, including computer vision, machine learning, and deep learning for manufacturing and energy sectors. - Solid knowledge of secure, sovereign cloud platforms and AI infrastructure tailored for compliance and data sovereignty. Digital & Operational Tools - Advanced proficiency in Gemini Enterprise, Gemini Agent Platform, and Google ADK. - Hands-on experience with Google Cloud Platform (GCP), Kubernetes management, and multi-cloud orchestration tools (IaaS, PaaS, MLaaS). Leadership Capabilities - Proven ability to manage, inspire, and scale a technical team of engineers to deliver high-quality digital solutions. - Exceptional communication skills to articulate complex AI concepts to both technical teams and business stakeholders. - Demonstrated capability in strategic planning, budgeting, and delivering major technology projects on time. - Mentorship mindset focused on continuous upskilling and fostering an innovative engineering culture. Required Qualifications & Experience - Minimum of 10-15 years of robust software engineering and AI/ML experience, with a specialized focus on Generative AI. - Deep, hands-on expertise within the GCP ecosystem, Gemini Enterprise, and the Gemini Agent Platform. - Proven experience in building, deploying, and maintaining AI agents using Google ADK, LangGraph, Crew.AI, or equivalent agentic frameworks. Educational Background - B.Tech or M.Tech in Computer Science, Artificial Intelligence, Software Engineering, or a strictly related quantitative field. - Advanced certifications in AI/ML, such as Google Cloud Professional Machine Learning Engineer, are highly preferred. Years & Type of Experience - 10-15 years of overall technical and engineering experience, with a significant portion dedicated to leading AI initiatives. - Proven track record of managing technical teams and deploying scalable machine learning architectures in complex enterprise environments. Key Responsibilities - Lead the end-to-end design, development, and deployment of Generative AI agents using Google ADK, LangGraph, and Crew.AI frameworks. - Architect scalable AI solutions within the Google Cloud Platform (GCP) ecosystem, leveraging Gemini Enterprise and the Gemini Agent Platform. - Manage and mentor a high-performing team of AI engineers to ensure the delivery of cutting-edge industrial AI solutions. - Collaborate with cross-functional teams to integrate generative AI models into sovereign cloud environments and industrial operations (such as energy, utilities, and manufacturing). - Drive the creation of robust Python-based AI pipelines for multi-cloud orchestration and real-time edge computing. - Establish best practices for AI model evaluation, prompt engineering, and agentic framework deployments across the organization. - Oversee the lifecycle of AI products from conceptualization to production, ensuring alignment with Adani AI Labs's strategic capabilities. - Troubleshoot complex AI/ML system bottlenecks and optimize model inference performance on GCP to enhance operational efficiency. Domain Expertise - Deep understanding of Generative AI, Large Language Models (LLMs), and complex agentic workflows. - Familiarity with industrial AI applications, including computer vision, machine learning, and deep learning for manufacturing and energy sectors. - Solid knowledge of secure, sovereign cloud platforms and AI infrastructure tailored for compliance and data sovereignty. Digital & Operational Tools - Advanced proficiency in Gemini Enterprise, Gemini Agent Platform, and Google ADK. - Hands-on experience with Google Cloud Platform (GCP), Kubernetes management, and multi-cloud orchestration tools (IaaS