Cloud Engineer, Data and AI
Confirmed on the employer's own hiring board on Nov 1, 2026. First seen by Alion on Oct 29, 2026. Google scores B on the Alion truth index.
About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI. You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers. Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you are the Google Engineer working with Google's largest and most ambitious Cloud customers. Together with the team you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
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.
Responsibilities
- Provide expert advisory on architectural frameworks and operational best practices for comprehensive Agentic platforms, encompassing deployment, monitoring, evaluation, governance, and security protocols.
- Lead comprehensive artificial intelligence initiatives through strategic thought leadership, while identifying agentic workflows and designing robust architectural solutions for advanced agentic implementations.
- Deliver effective big data and machine learning solutions and solve complex technical customer challenges.
- Identify new product features and feature gaps, provide guidance on existing product challenges, and collaborate with Product Managers and Engineers to influence the roadmap of Google Cloud Platform.
- Provide expert guidance on architectural data strategies to ensure optimized utilization across different AI models. Deliver best practices recommendations, tutorials, blog articles, and technical presentations adapting to different levels of key business and technical stakeholders.
Qualifications
Minimum qualifications:
- Bachelor's degree in Computer Science or equivalent practical experience.
- Experience architecting and deploying enterprise-grade cloud data platforms, incorporating both streaming and batch processing workflows.
- Experience writing software in Python, Scala, R, or similar.
- Experience with Gemini models, ADK, Gemini Enterprise, and other google AI products.
Preferred qualifications:
- 5 years of experience working with recommendation engines, data pipelines, or distributed machine learning.
- Experience with data analytics, data visualization techniques and software, and deep learning frameworks.
- Experience with core data science techniques.
- Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments.
- Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks.