Cloud AI Engineer, Google Cloud

The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.

As a Cloud AI Consultant, you will work directly with Google’s most strategic customers on critical projects to help them transform their businesses using AI/ML technologies. You will help customers to develop, deploy, and manage custom AI solutions in production using Google Cloud technologies. You will provide technical project management, consulting and technical aptitude to customer engagements while working with client executives and key technical leaders to deploy solutions on Google Cloud Platform. You will also work closely with key Google partners currently servicing top accounts to scope engagements, manage programs, deliver consulting services, and provide technical guidance and best practice expertise. You will possess a background in developing AI solutions, applying key industry tools, techniques, and methodologies.

In addition, to be successful, you will know how to navigate ambiguity, be a technical expert in your field, and deliver customer success. You will have excellent client-facing communication and project management skills.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

• 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.