Customer Engineer, Cloud AI, Financial Services, Google Cloud
As a Customer Engineer (CE) with a specialty in Cloud AI, Financial Services, you will partner with technical sales teams to differentiate Google Cloud to our customers. You will serve as a technical expert responsible for accelerating technical wins and adoption of complex, specialized workloads. You will leverage your expertise in our product areas, in partnership with Platform CEs, to be writing code to developing prototypes, proofs-of-concept, and demos to promote new, highly specialized solutions to customers. You will solve AI-centered customer issues and provide a critical feedback loop to influence product development.
You will have excellent organizational, communication, and presentation skills, engaging with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on Google Cloud. You will blend sales prowess, market knowledge, and technical engagement to show the value of the Google Cloud portfolio.
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: $152000 - $222000 (USD) + 42.86% bonus target + equity + benefits
Learn more about benefits at Google.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience with cloud native architecture in a customer-facing or support role.
- Experience with cloud engineering, on-premise engineering, virtualization, or containerization platforms.
- Experience engaging with, or presenting to, technical stakeholders or executive leaders.
- Experience in programming languages, debugging, systems design, prototyping, demos, or customer workshops.
Preferred qualifications:
- Master's degree in Computer Science, Engineering, Mathematics, a related technical field, or equivalent practical experience.
- Experience in building machine learning solutions and leveraging specific machine learning architectures (e.g., deep learning, long short-term memory (LSTM), convolutional networks).
- Experience in architecting and developing software or infrastructure for scalable, distributed systems.
- Experience with frameworks for deep learning (e.g., PyTorch, Tensorflow etc.), AI accelerators (e.g., TPUs), model architectures (e.g., encoders, decoders), or using machine learning APIs.
- Experience working within financial services industry.
Software pay context
Based on 7,857 disclosed Software salaries on RoleSuite, the role pays a median of $158K/year, with most offers between $123K and $200K (10th–90th percentile: $102K–$235K).
This posting lists $152K–$222K, above the $158K market median.
See the full Software salary breakdown →