Google Cloud AI Solutions Architect, Gemini Enterprise

We are seeking a hands‑on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and agentic AI solutions for end clients. This is a client‑facing technical delivery role focused on applied AI/ML implementation, not sales. The right candidate will have strong Google Cloud experience, hands‑on Gemini Enterprise or Google Cloud generative AI implementation experience, and the ability to translate client workflows into secure, scalable, production‑ready AI solutions. This person should be comfortable moving between architecture, coding, prototyping, configuration, integration, and client‑facing technical delivery. About the Role This role involves designing, building, configuring, and implementing Gemini Enterprise solutions for end clients, as well as developing AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows. Responsibilities Design, build, configure, and implement Gemini Enterprise solutions for end clients. Develop AI agent workflows that support business use cases, internal processes, enterprise automation, and operational workflows. Build prototypes and proofs of concept that can be iterated into production‑ready solutions. Design and implement applied AI/ML solutions using Gemini Enterprise, Vertex AI, and related Google Cloud AI services. Build and deploy LLM‑powered applications, AI agents, retrieval‑augmented generation workflows, and enterprise AI integrations. Evaluate model options, agent patterns, grounding strategies, retrieval approaches, and integration paths based on client use cases. Configure and deploy Gemini Enterprise agents, integrations, and related Google Cloud AI services. Integrate AI agents with enterprise systems, data sources, APIs, and business applications. Lead technical discovery with clients and translate requirements into solution architecture and implementation plans. Develop scripts, connectors, workflows, or lightweight applications needed to support AI agent implementation. Support model evaluation, prompt optimization, testing, validation, troubleshooting, and production readiness. Apply best practices for cloud security, IAM, data governance, responsible AI, monitoring, and enterprise deployment. Communicate technical recommendations clearly to client engineering, data, security, cloud, and business stakeholders. Qualifications Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, Machine Learning, or a related field; equivalent practical experience will also be considered. 5+ years of experience in cloud architecture, AI/ML solution architecture, technical consulting, solution architecture, software engineering, or hands‑on client‑facing technical delivery. 3+ years of experience working with Google Cloud Platform. Hands‑on experience implementing Gemini Enterprise or Google Cloud generative AI solutions. Hands‑on experience designing or implementing AI/ML solutions using Google Cloud AI services, including Vertex AI, Gemini, Gemini Enterprise, Agent Builder, Agent Development Kit, or related tools. Experience building, configuring, deploying, or integrating AI agents, generative AI applications, LLM‑powered applications, or enterprise AI workflows. Experience building agentic AI workflows using Google Cloud Agent Development Kit, Vertex AI Agent Engine, Agent Builder, or related agent development tools. Experience with core agentic AI implementation patterns such as retrieval‑augmented generation, prompt engineering, tool use/function calling, API integrations, enterprise system integration, and/or multi‑agent workflows. Experience with LLM application development, embeddings, model evaluation, prompt optimization, and production AI/ML implementation patterns. Strong understanding of Google Cloud AI and data services, such as Vertex AI, Gemini, Gemini Enterprise, BigQuery, BigQuery ML, Cloud Functions, Cloud Run, APIs, IAM, and related services. Ability to code, script, prototype, and troubleshoot technical solutions in client environments. Experience working directly with enterprise clients or internal business stakeholders to gather requirements and implement technical solutions. Strong understanding of cloud security, IAM, data governance, responsible AI, and enterprise deployment best practices. Excellent communication skills with the ability to explain complex technical concepts clearly. Must be a U.S. Citizen or Green Card holder. Required Skills Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands‑on implementation architect. Experience with data integration, workflow automation, enterprise applications, embeddings, vector search, semantic search, model grounding, enterprise search, or retrieval‑augmented generation pipelines. Experience in consulting, systems integration, professional services, or client‑facing technical delivery. Familiarity with infrastructure as code, CI/CD, containers, serverless architecture, and cloud‑native application deployment. Pay range and compensation package This position is open to direct candidates only. We are not working with third‑party agencies, subcontractors, or C2C arrangements for this role. Candidates must be U.S. Citizens or Green Card holders. Equal Opportunity Statement We are committed to diversity and inclusivity. #J-18808-Ljbffr The Data Sherpas