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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Austin, TX, USA; New York, NY, USA; San Jose, CA, USA.
Minimum qualifications: - Bachelor's degree or equivalent practical experience.
- 10 years of experience with technology, software engineering, or enterprise architecture, focusing on data engineering or AI/ML systems.
- Experience with designing and implementing data architecture frameworks, enterprise data warehouses/data lakes, or AI/ML pipelines.
- Experience with developing solution architectures and utilizing system design techniques.
Preferred qualifications: - Experience developing data and product strategies across a portfolio of internal systems within a complex enterprise.
- Expert-level knowledge of modern data tooling, cloud-native data services, MLOps frameworks, and large language model (LLM) orchestration patterns.
- Excellent organizational, analytical and influencing skills.
About the jobAs a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients or product partners. You will lead cross-functional teams in Engineering, Sales and Product Management to leverage emerging technologies for our external clients/partners. From concept design and testing to data analysis and support, you will oversee the technical execution and business operations of Google's online advertising platforms or product partnerships.
You will be able to balance business and partner needs with technical constraints, develop innovative, cutting edge solutions and act as a partner and consultant to those you are working with. You will also be able to build tools and automate products, oversee the technical execution and business operations of Google's partnerships, as well as develop product strategy and prioritize projects and resources.
We are seeking a highly technical, forward-thinking Enterprise Architect to join the Enterprise Product Strategy and Architecture (EPA) team with a dedicated focus on Data and AI Enablement. In this role, you will be responsible for defining, driving, and scaling enterprise-wide architectural standards, reference models, and patterns that empower Corporate Engineering to build innovative, secure, and data-driven capabilities.
You will be responsible for authoring the core reference architectures, blueprints, and design patterns required to modernize our data life-cycle and accelerate the deployment of safe, scalable AI solutions. This is an impact-driven role focused heavily on execution and enablement; you will work with technical leads and engineering squads across all Corporate Engineering pillars to advocate modern data architecture, unblock complex technical hurdles, and directly drive the active adoption of enterprise AI standards.
The Core team builds the technical foundation behind Google's flagship products. We are owners and advocates for the underlying design elements, developer platforms, product components, and infrastructure at Google. These are the essential building blocks for excellent, safe, and coherent experiences for our users and drive the pace of innovation for every developer. We look across Google's products to build central solutions, break down technical barriers and strengthen existing systems. As the Core team, we have a mandate and a unique opportunity to impact important technical decisions across the company.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $233000 - $325000 (USD) 25% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Author core blueprints, standardize AI patterns, and manage data governance and security parameters.
- Drive adoption and cross-pillar enablement by facilitating technical reviews and removing delivery friction.
- Collaborate with Environmental Protection Agency peers. Represent data/artificial intelligence at the executive architecture board.
- Evaluate industry trends and upskill engineering teams.
