Digital Transformation Consultant, AI Solutions, gTech

Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 6 years of experience in either system design or in one programming language (Java, C++, Python, etc.).
• 6 years of experience in technical troubleshooting, and managing internal/external partners or customers.

Preferred qualifications:

• Master's degree in Engineering or Business.
  
• Experience in one or more areas of Google Ads products.
  
• Knowledge of evolving tech/AI roadmap in support environments.
  
• Ability to identify and deploy tech solutions in partnership with regions, product, and tools teams.
  
• Excellent problem-solving skills, with the ability to synthesize data into useful formats and bring insights through communication.
  
• Excellent program management skills and ability to influence senior stakeholders.
  

About the job

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.

To learn more about gTech, check out our video.

The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Identify and evaluate potential AI use cases across all customer support functions. Conduct proof-of-concept projects to validate the feasibility and impact of proposed AI solutions.
• Collaborate with cross-functional teams to explore and experiment with new AI technologies and approaches. Contribute to a culture of innovation and continuous improvement within the team and the wider organization.
• Design, develop, and implement AI-powered solutions that address identified customer support challenges and collaborate with different engineering and product teams. Provide signals to partner teams to ensure efficient AI Operations and help refine models to improve their factuality and usefulness. 
• Develop plans to scale successful AI solutions across the entire Ads customer support organization. Identify opportunities for automation and process optimization using AI.
• Develop and improve scaled AI/ML model evaluation programs and AI Ops.