Sr Technical Solutions Consultant- Cloud (multiple openings)

Minimum qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field and 5 years of progressive, post-baccalaurate experience in the job offered or in a Technical Solutions Consultant-related occupation.
• Position requires the following: 5 years of experience in Production deployment or operations; 5 years of experience in Developing and maintaining production-grade systems in one of the following disciplines: Software development, Managing large scale Windows or Linux environments, Network or system design and deployment, Databases, or Storage systems; 2 years of experience in Delivering technical presentations to an executive or leadership audience; 2 years of experience in Project management, including budgets, timelines and stakeholder management; 1 year of experience in Reading a programming language: Python, Java, Go, or C++ and in Delivering in a Cloud context in any of: CSPs, AWS, or Azure.

About the job

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.

The US base salary range for this full-time position is $153,000 - $222,000 + 15.00% bonus target + equity + benefits determined by role, level, and location. Individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Learn more about benefits at Google.

Position reports to the Google Austin, TX office & may allow for a hybrid schedule as per Google policy.

Responsibilities

• Work with customer technical leads, client executives, and partners to scope, manage and deliver successful implementations of Cloud AI solutions, becoming a trusted advisor to decision makers throughout the engagement.
• Propose solution architectures and manage the deployment of cloud based machine learning solutions according to complex customer requirements and implementation best practices.
• Work with internal specialists, Product, and Engineering teams to package approaches, best practices, and lessons learned into thought leadership, methodologies, and published assets.
• Interact with Sales, Partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks and issues, and timelines for successful client outcomes.
• Domestic travel approximately 30% of the time for client engagements.