Engineering Manager (Generative AI)

To lead the Generative AI engineering initiatives at Adani AI Labs, focusing on developing intelligent agents and sovereign cloud AI solutions. This role drives the architectural design, implementation, and scaling of Generative AI applications that optimize operations across Adani’s industrial sectors, aligning with the vision to deliver secure, scalable, and intelligent digital transformation.

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.

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.

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.
• Strong knowledge of secure, sovereign cloud platforms and AI infrastructure tailored for compliance and data sovereignty.

Non-Negotiable Requirements

• Generative AI & Agentic Frameworks: Deep, hands-on understanding of building sophisticated AI agents using Google ADK, LangGraph, Crew.AI, or equivalent frameworks. The candidate must have a proven track record of deploying these agents in real-world, enterprise-scale scenarios.
• Advanced GCP & Gemini Ecosystem Mastery: Extensive experience operating within the Google Cloud Platform (GCP) ecosystem, with specialized expertise in Gemini Enterprise and the Gemini Agent Platform. Must be capable of designing resilient, sovereign cloud-compliant architectures.
• Python & Engineering Leadership: Exceptional background in Python programming combined with a demonstrated ability to manage and mentor high-performing engineering teams. Strong communication skills are essential to bridge the gap between complex AI technicalities and strategic business outcomes.

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.