Manager, Technical Solutions, Cloud Applied AI

Minimum qualifications:

• Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
• 10 years of experience in customer-facing technical roles (e.g., Solutions Architect, Forward Deployed Specialist, Principal Consultant) with a focus on enterprise systems.
• 6 years of experience writing code in one or more general purpose programming languages (e.g., C++, Java, Python, Go, etc).
• Experience with Large Language Models (LLMs), prompt development, and conversational AI frameworks.
• Experience with people management in a technical environment, or experience with mentoring and coaching team members.
  

Preferred qualifications:

• Master's degree in Engineering, Computer Science, or a related technical fields.
• Experience building and scaling complex production systems and working with multi-stakeholder technical projects, and with Google Cloud Platform (GCP) environment setup and cloud architecture.
• Experience with technical consulting and telecom customer deployments or related industries, including navigating governance, security, and procurement processes.
• 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.
• Excellent leadership skills, with an ability to motivate large teams in a changing environment.

About the job

Cloud Applied AI (AAI) powers business growth with Gemini Enterprise. Our portfolio includes Gemini Enterprise for Customer Experience, along with other vertical and domain packaged solutions. We enable high adoption and speed to value by building 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 with unprecedented speed.

In this role, you will oversee technical solutions consultants across multiple customer deployments, and are a high-visibility multiplier responsible for turning the promise of Agentic AI into production reality for Google’s most global customers. You will sit at the nexus of Product, Developing, and the Customer, translating complex business friction into elegant, reasoning-based AI solutions.

You will contribute to the end-to-end delivery of agentic solutions, working with a group of deployment specialists to implement best practices for delivering at scale and velocity. You will be a builder, a systems thinker, and a master of navigating complex technical and business issues and will guide, mentor and scale your team for direct customer impact. You will be working with a group of deployment specialists while simultaneously incubating new products and defining the best practices that will enable the entire Google Cloud ecosystem.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $233000 - $325000 (USD) + 25% bonus target + equity + benefits
Canada: $248000 - $255000 (CAD) + 25% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Lead and scale a high-performing developing team to deliver 0-to-1 agentic solutions, maintaining an approach to debugging, prompt developing, and framework standardization.
• Drive direct customer engagements and resolve high-stakes escalations, providing authoritative architectural guidance to client developing teams and C-suite executives.
• Pioneer advanced agent architectures (such as Agent-MVC) and safely integrate non-deterministic LLM outputs with deterministic enterprise systems like SAP and Salesforce.
• Stress-test pre-GA features in real-world environments, synthesizing field intelligence to directly influence Google Cloud Product and Developing roadmaps.
• Establish evaluation pipelines (utilizing Gold Datasets and Judge frameworks) to benchmark agent performance while managing third-party vendor and delivery partners.