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Open nowFirst seen 11 hours ago

Customer Engineering Manager, Cloud AI, Financial Services, Google Cloud

Google3,111 open roles

Where
New York, NY, USA
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Your applicationOpen nowCustomer Engineering Manager, Cloud AI, Financial Services, Google CloudGoogle · New York, NY, USA
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The clock on this job

Early applications get read.

8.0% of postings close within 7 days. Measured by our own scanner across the market. Google postings stay open a median of 27 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.6%3 days
  3. 8.0%7 days
  4. 15.0%14 days
  5. 34.2%30 days
This job: first seen 11 hours ago

Google median: 27 days open

The posting

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • Leadership experience (e.g., people management, team lead, mentorship, coaching).
  • Experience with AI agent orchestration frameworks (e.g., LangGraph, CrewAI, AutoGen), agentic design patterns (e.g., tool-use, multi-agent collaboration), machine learning, or integrating models into autonomous workflows via advanced API prompting or RAG.
  • Experience with technical conversations, demos, prototyping, or workshops with customers.

Preferred qualifications:

  • Master's degree in Computer Science, Engineering, Mathematics, or a technical field.
  • Experience supporting Financial Services customers.
  • Experience as a pre-sales manager or technical customer-facing people manager within a professional services or sales engineering team.
  • Experience influencing cross-functional teams (e.g., Product Management, Engineering, Sales, Marketing, Partner), customers, and partners to impact business goals, customer experience, and customer expansion.
  • Experience tailoring and delivering compelling messages by audience, asking questions, and leading conversations that accelerate value realization and business opportunity.

About the job

As a Customer Engineering (CE) Manager for Financial Services with a specialty in Cloud AI, you lead and deploy a team of subject matter experts responsible for working alongside our customers to provide trusted technical and solution advice to accelerate workload migration and remove technical blockers. You will foster a culture of technical excellence and understand the mechanics of architecture, delivery, and consumption within your specialized domain and Google Cloud’s products and solutions.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: $192000 - $267000 (USD) + 42.86% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

  • Lead a team of Cloud AI Customer Engineers, focusing on team culture, talent strategy, and skills development to deliver successful cloud transformations for customers and accelerate value realization.
  • Foster customer partnership and provide thought leadership related to cloud, transformation, and highly specialized technical solutions in your practice to drive technical wins.
  • Partner with Sales to define technical go-to-market strategies and delivery plans, focusing on advanced workload adoption and repeatable solution development.
  • Balance technical leadership with operational excellence; lead workload and opportunity review meetings and provide insight into how to achieve technical wins and migration strategy, working directly with customers, partners, and prospects. Oversee domain-specific prototyping and proofs-of-concept.
  • Work cross-functionally across Google, partners, and your team to resolve technical roadblocks, and provide critical feedback loops to Product and Engineering based on field experience.
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