Technical Solutions Architect, Internal Enterprise Product Strategy

As a Technical Solutions Consultant, you will be responsible for the technical relationship of our largest advertising clients and/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 and/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: $183000 - $266000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google.

• Partner closely with other enterprise architects to ensure data and AI standards seamlessly integrate with broader enterprise platforms, applications, and core infrastructure.
• Collaborate with pillar leads and engineering teams to embed established data and AI reference patterns into their localized system designs. Lead technical forums, architecture deep-dives, and workshops to elevate data engineering and AI competencies.
• Review data and AI proposals, proactively identifying architectural fragmentation, and mitigating security threats or technical debt. Serve as the technical bridge between centralized AI infrastructure and distributed pillar squads, unblocking architectural dependencies and driving execution.
• Define architectural guidelines that ensure robust data privacy, compliance, metadata management, and model lineage standards are deeply integrated into all technical designs.
  
• Evaluate emerging technologies, industry trends, and third-party solutions, actively bringing them to bear to provide a strategic advantage across the portfolio.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in technology, software engineering, or enterprise architecture, with an emphasis on data engineering or AI/ML systems.
  
• Experience designing and implementing data architecture frameworks, enterprise data warehouses/data lakes, or production-grade AI/ML pipelines.
• Experience in developing solution architectures through system design techniques (sample topics include distributed systems, designing a system under certain constraints, simplicity, limitations, robustness and tradeoffs).

Preferred qualifications:

• Experience with modern system design patterns (e.g., microservices, event-driven architectures, Zero Trust security models, cloud-native scalability) and their integration with large-scale enterprise portfolios.
• Experience developing architectural strategies across a portfolio of internal systems within a complex, highly regulated global organization of large-scale.
• Demonstrated ability to operate effectively within an established central enterprise architecture function, balancing individual pillar delivery and velocity with shared enterprise goals.