The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
The AI Strategic Pursuits team is a specialized product incubation engine dedicated to accelerating product market fit for the Generative AI capabilities in Google Cloud. Composed of expert builders and product leaders, this team focuses on solving the integration and last-mile issues that define the next generation of enterprise data architectures, directly de-risking the roadmap for the broader organization.
In this role, you are tasked with bridging the gap between the powerful platform primitives and the cohesive, high-value solutions enterprises demand, this group operates as a customer-zero laboratory. Operating on a high-impact co-invest, build, codify flywheel, you will embed with a select group of lighthouse customers to co-develop breakthrough solutions in real-world environments. Rather than stopping at individual customer success, your primary mandate is to translate these engagements into scalable assets delivering validated product prototypes to engineering and repeatable go-to-market (GTM) blueprints to the field.
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 $234,000-$325,000 + 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.
Responsibilities
- Architect lighthouse customer projects, design integrations with Gemini and Vertex AI to build high-value solutions like agentic workflows and semantic data layers.
- Resolve ambiguous technical hurdles and optimize latency. Bridge disparate systems, architect security and governance layers that transform experimental demos into production-ready assets.
- Transform bespoke solutions into reusable assets. Write golden path repositories and reference architectures, enable partner and customer engineering to scale your work.
- Serve as the technical source of truth. Document Application Programming Interface (API) friction and product gaps discovered during deployment to directly influence roadmaps for Gemini Cloud Assist and Cloud Hub.
- Mentor multiple builder engineers while advising customer Chief Technology Officers (CTOs). Establish coding standards and validate feasibility to align the architectures with complex enterprise stacks.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 10 years of experience in project managing and delivering technical solutions.
- Experience in one or more discipline areas: machine learning, recommendation systems, natural language processing, computer vision, pattern recognition, or artificial intelligence.
- Experience with technical client service (e.g., consulting).
- Ability to communicate in English fluently to support client relationship management in this region.
Preferred qualifications:
- Experience in systems design.
- Experience designing and deploying with one or more from the following technologies: TensorFlow, Spark ML, CNTK, Torch, Caffe, Scikit-learn.
- Experience in a statistical programming language like R or Python and applied Machine Learning (ML) techniques (e.g., dimensionality reduction strategies, classification, and natural language processing frameworks).
- Ability to architect and explain data analytics pipelines and data flows.
- Excellent communication, presentation and problem-solving skills.