Google Cloud Engineer developing secure Google Cloud environments for Gemini Enterprise Customer Experience solutions. Leading innovative solutions for AI-powered customer experience transformation.
Responsibilities
Stay current on Google CES advancements, generative AI, and NLP trends to recommend and integrate new capabilities.
Contribute to the development of innovative solutions and accelerators on the Google CES platform.
Ensure delivery excellence and solution scalability by applying best practices and proven technical approaches.
Encourage a culture of innovation and continuous improvement within the team.
Lead the architecture and development of Google Cloud environments specifically optimized for Gemini Enterprise Customer Experience (GECX) deployments.
Design and implement secure integrations between GECX, Google Cloud AI services and external platforms.
Configure identity and access management (IAM) and secure service accounts to ensure governed access to GECX components.
Requirements
Bachelor’s degree in Computer Science, Engineering, Business, or related field; advanced degree is an asset.
5+ years of experience in technology consulting, digital transformation, or customer experience, with a focus on AI/ML solutions.
Preferred: Active Google Cloud Professional Certifications such as Professional Cloud Architect, Professional Machine Learning Engineer, or Professional Data Engineer.
Practical expertise with Google Customer Engagement Services (formerly CCAI).
Proven success delivering AI/ML-powered customer engagement or contact center solutions.
Strong understanding of customer experience design, contact center operations, and key CX metrics.
Excellent communication and presentation skills for both executive and technical audiences.
Senior Cloud Architect designing resilient, secure cloud infrastructure for Intelex's SaaS platform. Leading cloud migration initiatives and collaborating with engineering and AI teams on best practices.
Engineer II on Cloud Delivery team at TJX Canada, implementing cloud solutions and collaborating with business teams. Focused on enhancing capabilities using cloud technologies.
Lead the design of next - generation cloud, data, and AI - powered platforms as a Systems Architect. Shape strategy and execution across Azure, Kubernetes, microservices, and AI/ML systems.