About the job

When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.

As a Platform Customer Engineer (CE), you will partner with technical Sales teams to differentiate Google Cloud to our customers. You will serve as the customer’s primary technical partner and trusted advisor, engaging in technical-led conversations to understand their business challenges. You will troubleshoot technical questions and roadblocks, engage in proofs of concepts and demos, and use your expertise to architect cross-pillar cloud solutions that solve these business challenges. You will drive the technical win and define the delivery and consumption plans. You will engage with technical and business leaders, and persuasively present practical and useful solutions on Google Cloud. You will focus on identifying, pursuing, and winning new business workloads.

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.

The US base salary range for this full-time position is $127,000-$184,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Develop and own the technical account plan and strategy, participating in planning and supporting targeted sales motions.

• Combine sales, programming, and solutions architecture expertise to prove the value of Google Cloud Platform across the portfolio through complex demos, pilots and in-depth workshops.

• Architect cross-pillar solutions, drive technical wins, and define initial delivery plans for customers. Lead the technical engagement in the solution phase.

• Facilitate the post-sales transition by supporting pricing activities and transitioning the final delivery plan to implementation teams.

• Maintain awareness of progress against the delivery plan, providing support to cross-functional teams during ramp, delivery, migration or implementation phases.

Minimum qualifications

• Bachelor's degree or equivalent practical experience.

• 6 years of experience with cloud native architecture or AI systems in a customer-facing or support role.

• Experience identifying AI use cases to solve customer challenges or selling AI technology.

• Experience engaging with, or presenting to, technical stakeholders or executive leaders.

• Technical expertise to lead workshops, develop prototypes, and conduct demonstrations for clients.

Preferred qualifications

• Experience navigating AI infrastructure consumption models and optimizing high-throughput training/inference clusters.

• Experience implementing multi-agent systems using frameworks (e.g., A2A, Lang Graph, CrewAI, Auto Gen).

• Experience navigating the startup lifecycle, from initial prototyping with AI Studio to scaling and achieving product-market fit on Vertex AI.

• Experience working with, and a passion for, the high-growth startup ecosystem and its typical rapid-scaling challenges.

• Knowledge of "LLM-native" performance metrics (TTFT, tokens/sec, cost-per-request) and techniques for optimizing state management, quantization, and provisioned throughput.

• Ability to implement secure agentic workflows incorporating MCP, tool-calling, and enterprise-grade authentication.