Cloud AI Engineer, Google Cloud
Summary
As a Cloud AI Consultant at Google, you will design and deploy production-grade Generative AI solutions for strategic enterprise customers. You will work with Gemini Enterprise, Agent Development Kits, and Python to build agentic architectures and RAG systems on Google Cloud Platform, while providing technical leadership and C-suite advisory.
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.
- 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.