> Markdown version of [/jobs/ext/2360531-google-ai-architect](https://www.wearedevelopers.com/jobs/ext/2360531-google-ai-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Google AI Architect - **Company:** Deloitte T.T.L. - **Location:** Sacramento, CA, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, BigQuery, Cloud Computing, Cloud Database, Continuous Integration, Software Design Patterns, Github, Network Security, Machine Learning, Software Deployment, Google Cloud, Feature Engineering, Autoscaling, Large Language Models, Build Server, Containerization, AI Platforms, Google Cloud Functions, Machine Learning Operations, Terraform, Data Pipelines, Devsecops, Serverless Computing, Jenkins, Microservices - **Published:** August 9, 2026 - **Apply:** https://us.experteer.com/career/view-jobs/google-ai-architect-sacramento-ca-usa-58862206 ## About the Role advance and governance for AI/ML systems, including data privacy and safety measures * Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines * Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform * Apply and enforce design patterns for resilient software and agentic architectures Tasks * Bachelor's degree in a technical field * 6+ years as Software or Solution Architect with production-scale experience * 5+ years hands-on Google Cloud experience with 2+ end-to-end enterprise implementations * 4+ years Terraform-based Google Cloud networks and security * 2+ years containerized workloads on GKE with autoscaling and observability * 2+ years CI/CD/DevSecOps with Cloud Build, GitHub Actions or Jenkins * 3+ years migration or modernization to Google Cloud * 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, aa aaaaaA_ production deployment Key requirements * ## Description Experteer Overview In this role you will architect and deliver enterprise AI platforms on Google Cloud, leveraging Vertex AI and Gemini to scale production solutions. You'll align AI initiatives with the wider tech strategy, shaping data pipelines, model lifecycles, and CI/CD pipelines. You'll lead secure, governance-aware deployments and drive GenAI-enabled software across diverse client environments. This is a high-impact opportunity to advance AI-driven transformation at scale within a leading consulting firm. Compensation / Benefits * Architect and design enterprise-grade AI applications and platforms for production-scale deployment * Integrate and fine-tune LLMs and AI/ML models into enterprise apps with production-grade deployment, inference, and monitoring * Collaborate with enterprise architects to ensure AI solutions align with governance and standards * Develop cloud-native solutions on hyperscalers (GCP/AWS/Azure) using containers, serverless, and managed DBs * Implement security and governance for AI/ML systems, including data privacy and safety measures * Define end-to-end architectures across data pipelines, feature engineering, model lifecycle, APIs/microservices, and CI/CD/MLOps/LLMOps with Vertex AI Pipelines * Lead cloud-native development on GKE, Cloud Run, Pub/Sub, BigQuery, Cloud SQL/Spanner, Memorystore, and Terraform * Apply and enforce design patterns for resilient software and agentic architectures Tasks * Bachelor's degree in a technical field * 6+ years as Software or Solution Architect with production-scale experience * 5+ years hands-on Google Cloud experience with 2+ end-to-end enterprise implementations * 4+ years Terraform-based Google Cloud networks and security * 2+ years containerized workloads on GKE with autoscaling and observability * 2+ years CI/CD/DevSecOps with Cloud Build, GitHub Actions or Jenkins * 3+ years migration or modernization to Google Cloud * 2+ years applying AI/GenAI on Google Cloud with Vertex AI and Gemini, including production deployment Key requirements * ## Related Videos - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [Data Governance in the Era of AI](https://www.wearedevelopers.com/videos/1622-data-governance-in-the-era-of-ai) - [Making Data Warehouses fast. 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