The Google Cloud Applied AI (AAI) Solutions Consulting Team functions as a high-stakes unit responsible for Google's most strategic AI deployments. We bridge the gap between experimental AI and enterprise reality, acting as the technical and strategic engine that turns complex business problems into production-ready agentic solutions. As an AI Solutions Engagement Manager, you are a technical solutions consultant across multiple customer deployments, and a high-visibility team multiplier responsible for turning the promise of Agentic AI into production reality for Google's most strategic global customers. You sit at the nexus of Product, Engineering, and the Customer, translating complex business friction into elegant, reasoning-based AI solutions. Responsibilities Contribute to technical engagements from 0-to-1, defining the agent's reasoning paths, API tools, and guardrails to ensure resilient, autonomous infrastructure. Mitigate high-stakes customer escalations, providing direct debugging and architectural guidance to customer engineering and C-suite teams. Deploy pre-general availability features in real-world environments to stress-test capabilities, synthesizing field intelligence to directly influence the Google Cloud Product and Engineering roadmaps. Advocate for foundational architectural frameworks such as Agent-MVC and pioneer advanced techniques like meta-prompting and cyclic reasoning loops to accelerate time-to-value. Bridge the gap between non-deterministic LLM outputs and deterministic enterprise systems (e.g., SAP, Salesforce) to ensure safe, reliable agentic operations within rigid guardrails. Minimum Qualifications Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 7 years of experience in customer-facing technical roles (e.g., Solutions Architect, Forward Deployed Engineer, or Principal Consultant). 3 years of experience in system architecture and reading code (e.g., Python). Experience with Large Language Models (LLMs), prompt engineering, and conversational AI frameworks. Preferred Qualifications Master's degree in Engineering, Computer Science, or related technical fields. Experience building and scaling complex production systems and working with multi-stakeholder technical projects, and with GCP environment setup and cloud architecture. Experience in technical consulting, navigating the governance, security, and procurement complexities of Fortune 500 environments. Ability to bridge the gap between LLM capabilities and deterministic enterprise systems (e.g., Salesforce, SAP). Ability to lead cross-functional teams and influence executive stakeholders in large, cross-functional organizations. The Canada base salary range for this full-time position is CAD 195,000–200,000 + bonus + equity + benefits. Bachelor's degree in STEM or equivalent practical experience; 7 years in customer-facing technical roles; 3 years in system architecture and code reading (Python); experience with LLMs, prompt engineering, and conversational AI frameworks. #J-18808-Ljbffr