Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas • Atlanta, GA

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About The Position

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.

Requirements

• 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.

Nice To Haves

• Google Cloud Generative AI Leader certification.
• Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.
• Experience as a Forward Deployed Engineer, Solutions Architect, AI Architect, ML Engineer, Customer Engineer, Technical Consultant, or hands-on implementation architect.
• Experience with Python, JavaScript, TypeScript, or similar programming languages.
• 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.

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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior