Solutions Architect, Google Cloud, Conversational AI
- Full Time
- Other
- Remote-US
- $100K - $200K
Remote Job Description
As Solutions Architect - Conversational AI, you will contribute to Google’s innovations of Contact Center AI (CCAI) solutions for our customers and partners. You will create proof of concepts and prototypes with the newest Gen AI capabilities and innovative virtual agent solutions, using LLM-driven capabilities in Contact Center AI to enable digital transformation for our customers and partners.
In this role, you will maintain close partnership with Google’s Engineering teams to build and constantly drive excellence in our products. In addition, you will work with Google’s most strategic Cloud customers. You will represent Google Cloud AI as a Conversational AI expert during pre-sales, and serve as a trusted advisor on Conversational AI products to our partners in Sales, Professional Services, and Customer Engineers. This involves traveling to customer sites to provide consulting, advisory, and implementing solutions.
Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. 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 $140,000-$209,000 + 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
- Build solutions and pilot private preview AI features with early access partners and customers.
- Take responsibility for leading technical pilots and pre-sales pursuits with customers, including activities such as technology advocacy, product and solution briefings, proof-of-concept work, and the coordination of supporting technical resources.
- Prepare and deliver product messaging to highlight the Google Cloud AI value proposition, using techniques that include whiteboard and slide presentations, product demonstrations, white papers, and Request for Information.
- Collaborate with the Product and Engineering teams to identify product gaps, and work with cross-functional teams to design solutions.
Note: Google’s hybrid workplace includes remote and in-office roles. By applying to this position you will have an opportunity to share your preferred working location from the following:
In-office locations: Reston, VA, USA; Austin, TX, USA; Boulder, CO, USA; New York, NY, USA; Sunnyvale, CA, USA.
Remote location(s): California, USA; Colorado, USA; Texas, USA.
Qualifications
Minimum qualifications:
- Bachelor’s degree 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.
- Experience building solutions with Conversational AI technology (chatbots or vociebots).
Preferred qualifications:
- Master’s degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science, or a related field.
- Certified Machine Learning Engineer.
- 8 years of experience in a customer-facing role.
- Experience with all phases of a Machine Learning project delivery (from data collection to production deployment at scale).
- Experience building, integrating, and deploying complex Contact Center solutions
- Excellent leadership and influencing skills in the application of AI or Machine Learning.