Generative AI Technical Solutions Consultant

3 Months ago • 3-5 Years • Artificial Intelligence

Job Summary

Job Description

As a Generative AI Technical Solutions Consultant at Google Cloud, you will be part of the Applied AI Engineering/Cloud AI team responsible for delivering large-scale GenAI solutions. You will develop reusable solutions accelerators and build GenAI apps to onboard and scale customer engagements. This involves collaborating with product teams, bridging product gaps, and creating reusable assets like "talk to docs," "talk to data," and "talk to code." You'll also build automated prompt optimization tools and work with Google Deepmind to adapt Gemini for enterprise use. Responsibilities include cross-functional collaboration with Google Cloud AI teams, solving complex customer use cases using Cloud AI conversational products, creating reusable assets, delivering training, discussing functional/technical topics with stakeholders, and acting as a trusted advisor to customers.
Must have:
  • Bachelor's degree in STEM or equivalent
  • 3+ years Generative AI experience
  • 2+ years coding experience (Python, Java)
  • Cloud & AI platform experience
  • Collaborate cross-functionally
  • Solve complex customer use cases
  • Create reusable assets & training
Good to have:
  • Master's degree in related field
  • Experience in Conversational AI, Telecommunications, or Contact Centers
  • Consulting experience
  • Knowledge of TensorFlow

Job Details


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.

Preferred qualifications:

  • 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.
  • Knowledge of other AI frameworks, products, or solutions such as TensorFlow.
  • Ability to lead and organize the design and implementation of AI-based custom developed cloud solutions.

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-functionally with 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 topics with 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.

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