Staff AI Solutions Deployment Developer - Google, Waterloo

AI Summary

Google is seeking a Staff AI Solutions Deployment Developer in Waterloo, ON, Canada. This technical role involves contributing to AI solutions, mitigating high-stakes customer escalations, and deploying pre-general availability features. Candidates require a bachelor's degree or equivalent, eight years of customer-facing technical experience with enterprise systems, and three years of coding experience, alongside expertise in Large Language Models.

About the Role and Impact at Google Cloud

As a Staff AI Solutions Deployment Developer at Google, you will play a pivotal role within the Cloud Applied AI team, which powers business growth through innovative offerings like Gemini Enterprise. This team is dedicated to enabling high adoption and speed to value by crafting solutions that are quickly deployed, delivering new 0-to-1 capabilities with startup agility. Team members operate at the forefront of AI, collaborating directly with model builders at unprecedented speed. In this capacity, you will serve as a crucial technical solutions consultant across multiple customer deployments, acting as a high-visibility team multiplier responsible for transforming the promise of Agentic AI into a production reality for Google’s most strategic global customers. Your deep technical experience will be essential in bridging the connection between product, development, and the customer, translating complex business friction into elegant, reasoning-based AI solutions that integrate seamlessly with existing enterprise systems. This role offers a unique opportunity to contribute significantly to the Google Cloud ecosystem, defining best practices and incubating new products.

Core Responsibilities and Required Experience

In this challenging role, you will contribute to the end-to-end delivery of agentic solutions, working alongside a group of deployment specialists to implement best practices for delivering at scale and velocity. A key aspect of your responsibilities will involve contributing to technical engagements from their inception, defining the agent’s brain (reasoning paths), hands (API tools), and guardrails to ensure resilient, autonomous infrastructure. You will also be tasked with mitigating high-stakes customer escalations, providing direct debugging and architectural guidance to customer developers and C-suite teams. Deploying pre-general availability features in real-world environments to stress-test capabilities is another critical duty, where you will synthesize field intelligence to directly influence the Google Cloud Product and Developer roadmaps. Furthermore, you will advocate for foundational architectural frameworks such as Agent-MVC and pioneer advanced techniques like cyclic reasoning loops to accelerate time-to-value. A significant part of your technical expertise will be applied to bridging the gap between non-deterministic Large Language Model (LLM) outputs and deterministic enterprise systems, such as SAP and Salesforce, to ensure safe, reliable agentic operations within established guardrails. This requires substantial experience in navigating complex technical and business challenges.