Partner Technical Activation Lead, Cloud AI

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 9 years of experience working with a variety of enterprise and cloud technology systems, designing solutions, or developing business applications.
• Experience in supporting demanding enterprise customers with platform or application products, balancing customer requirements and product features/design.
• Experience working with predictive and generative AI tooling such as Large Language Models (LLMs), MLOps, RAG and Grounding, and Agentic Frameworks such as LangChain, GenAI evaluation services.

Preferred qualifications:

• Master’s degree in Business, Statistics, Mathematics, Economics, Engineering or Applied Science, or a related field.
  
• Experience with all phases of a machine learning project delivery from data collection to production deployment at scale.
• Experience using a consultative approach to drive technically projects in enterprise environments, with a detailed understanding of expectations from PoC to production.
• Experience in driving multiple teams to manage problems by evaluating internal and external risk of action plans.
• Excellent communication, writing, presentation, and problem-solving skills.
• Excellent cross-functional leadership skills.

About the job

As you develop a technical deep understanding of our Agent Builder, Search and Agentspace product portfolio, you will be the connector between Cloud AI product teams and our prioritized partners. By leveraging your technical expertise in (Gen) AI, you will orchestrate expert support to these partners across our portfolio of our joint go-to-market initiatives. You will also design and lead the technical implementation of these products in our own day-to-day interactions with business teams.

As a technical consultant embedded within product management, you will lead the integration of cross-functional projects, manage problems by evaluating internal and external risk of action plans, apply knowledge of intersection between Google’s technologies, its business goals, and the industry, and ultimately impact Cloud AI growth and partner satisfaction.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

The US base salary range for this full-time position is $177,000-$263,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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. 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

• Design and lead the implementation of Cloud AI technologies in our day-to-day interactions as product managers with customer-facing teams (e.g., Office of Personnel Management (OPM) chat bot and other use cases).
• Design and execute programs bringing implementation partners early in the product life cycle, to accelerate our Go-To-Market (GTM) reach and product usage ramp-up after launch.
• Distill target partners technical feedback on the products, in order to unblock business. Represent Product Management and Engineering in interactions with partners as they craft their own offerings and build on our products, as well as in technical feedback sessions.
• Collaborate with Google Cloud Partner Engineering teams and unblock business accordingly, to represent these targeted partners back to product management and engineering.