Minimum qualifications:
- Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience.
- 3 years of experience with Generative AI, Large Language Models (LLMs), Machine Learning, and related frameworks.
- 2 years of experience writing code in one or more programming languages (e.g., Python, Java).
- Experience working with Cloud and AI Platforms.
- Master's degree in Engineering, Computer Science, or related technical fields.
- Experience in Conversational AI, telecommunications, networking, or contact centers.
- Experience in consulting, technical consulting in a customer-facing role, with solid results working with a variety of different types of customers, engineers, and business.
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About the job
As part of Applied AI Engineering/Cloud AI, the team is responsible for large-scale last mile GenAI solutions delivery. We develop reusable horizontal solutions accelerators and build GenAI apps to onboard and scale customer engagements.
These scalable reusable solutions accelerators enable Google Cloud Platform (GCP) customers to deploy Generative AI solutions easily and with high accuracy. We collaborate with product teams and bridge gaps in products using this repeatable solutions accelerator methodology. Examples of reusable artifacts include "talk to docs", "talk to data", "talk to code", etc. We also build automated prompt optimization tools. Finally, we also work with Google Deepmind and other research teams to make Gemini suitable for enterprise use cases when accessed from Vertex AI.
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
- Collaborate cross-functionallywith Google Cloud AI teams (e.g., product, engineering, sales, professional services, learning, etc.).
- Solve complex customer use cases using Cloud AI conversational products to drive broad customer adoption, creates reusable assets (e.g., code, toolkits, training), and deliver training for new product features or solutions for customers, partners, and field teams.
- Discuss functional, technical, and basic commercial topicswith customer stakeholders(e.g., developers, line managers)and empathize, shape, and influence them.
- Work closely with customer stakeholders as a trusted advisor and provides expert guidance on critical solution decisions.