About the job
As an AI Architect, you will be the technical "tip of the spear" for Google’s AI partnership strategy. You will act as an entrepreneurial architect, making Gemini Enterprise a reality within our partners' unique environments. You will provide support, co-build, and solve the "impossible" technical hurdles that prevent partners from reaching production at scale. Your work will directly impact how the world's largest organizations adopt Google’s AI ecosystem, accelerating the transition from pilot projects to enterprise-wide production value. Additionally, you will provide industry expertise in public cloud platforms and technologies, with a particular emphasis on Sovereign Cloud and AI capabilities.
Responsibilities
Manage technical co-innovation with Google Cloud’s partners to architect and deploy generative Artificial Intelligence (AI) solutions (specifically Sovereign Cloud) and AI capabilities in high-scale environments.
Provide in-depth Sovereign and AI expertise and build joint product capabilities with Google’s strategic partners across solution pillars (e.g., AI, Sovereign, Security DevOps, Analytics).
Identify and solve architectural bottlenecks that hinder partner deployment velocity, ranging from model steering and API performance to hybrid-cloud integration constraints.
Build bespoke integration works into versioned, validated deployment baselines that can be scaled across the global partner ecosystem.
Act as an entrepreneurial technical, guide partner chief technology officer and principal engineer on the "art of the possible" and long-term AI strategy.
Collaborate with internal product and engineering teams to feed partner requirements back into the development cycle, ensuring Google’s AI tools are enterprise-ready.
Qualifications
Minimum
Bachelor’s degree in Computer Science, Science, Technology, Engineering and Mathematics, or equivalent practical experience.
7 years of experience in cloud computing architecture, software engineering, or technical consulting.
Experience in a partner-facing, customer-facing, or product management role bridging technical execution with business strategy.
Experience in either system design or reading code (e.g., Java, C++, Python).
Experience in cloud solutions architecture across Kubernetes, Container based applications, IaaC, security and networking.
Preferred
5 years of experience architecting or leading the deployment of Enterprise AI/ML solutions, with in Multi-Agent Systems (MAS), reasoning engines, and advanced model steering.
Experience resolving integration hurdles in Identity Orchestration (OAuth 2.0, OIDC, SAML) and cross-tenant security hardening (e.g., VPC-SC, IAM) within multi-tenant SaaS environments.
Experience with production-grade RAG, Vector Databases (ScaNN/HNSW), and high-scale data interoperability (e.g., BigQuery Zero-Copy, AlloyDB).
Experience defining user journeys, conducting gap analysis on technical platforms, and translating partner friction into prioritized product requirements documents to influence internal engineering roadmaps.
Experience with Sovereign Cloud and automation tools (Terraform or Ansible).