Cloud AI Engineer, Google Cloud

• Act as a thought leader and mentor across the Google Cloud organization, elevating the technical acumen of engineers and shaping best practices for agentic AI architectures.
• Oversee the global delivery and implementation of Gemini Enterprise solutions, utilizing Agent Development Kits (ADKs) to solve highly complex, enterprise-scale technical challenges.
• Serve as the trusted technical advisor to C-suite executives at Google’s most strategic global accounts, shaping their overarching AI strategy and accelerating the adoption of Gemini Enterprise.
• Translate complex architectural challenges into actionable requirements for Google's engineering teams, influencing the core product roadmap.
• Deliver leading practice recommendations and high-stakes technical presentations to executive boards and key business stakeholders to secure massive-scale technical wins.

Minimum qualifications:

• Bachelor's degree in Computer Science, related field, or equivalent practical experience.
• 5 years of experience in software engineering, cloud architecture, or technical consulting.
• 2 years of experience deploying production Generative AI (GenAI) applications.
• Experience building and orchestrating agents using Agent Development Kits (ADKs) or frameworks (LangChain, LlamaIndex, AutoGen).
• Experience in Python and cloud computing principles (serverless, virtualization, secure networking).

Preferred qualifications:

• Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
• Relevant Google Cloud certifications, such as Professional Cloud Architect or Professional Machine Learning Engineer.
• Experience deploying enterprise GenAI platforms (Gemini Enterprise), with deep understanding of AI security, governance, and compliance standards.
• Experience leveraging Large Language Model (LLMs) to deploy enterprise-scale multimodal solutions across text, image, video, and audio.
• Advanced experience implementing scalable RAG architectures connected to external productivity tools and enterprise databases.
• Experience leading engineering teams to design modern architectures (APIs, microservices) and deploy enterprise-scale cloud transformations with integrated AI models.

• Bachelor's degree in Computer Science, related field, or equivalent practical experience.
• 5 years of experience in software engineering, cloud architecture, or technical consulting.
• 2 years of experience deploying production Generative AI (GenAI) applications.
• Experience building and orchestrating agents using Agent Development Kits (ADKs) or frameworks (LangChain, LlamaIndex, AutoGen).
• Experience in Python and cloud computing principles (serverless, virtualization, secure networking).