Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas; Atlanta (GA); On-site; USD 150,000 - 210,000; Full time

Job summary

The Data Sherpas seeks a hands-on Google Cloud AI Solutions Architect to design, build, configure, and implement Gemini Enterprise and related AI solutions for end clients. This client-facing role focuses on applied AI/ML implementation and production-ready delivery.

Ideal candidates have strong Google Cloud experience, hands-on Gemini Enterprise experience, and can translate client workflows into scalable AI architectures.

Qualifications

• Bachelor's degree or equivalent practical experience in a technical field.
• 5+ years in cloud architecture, AI/ML solution design, or client-facing delivery.
• 3+ years with Google Cloud Platform and related certifications.
• Hands-on Gemini Enterprise or Google Cloud generative AI implementation experience.

Responsibilities

• Design, build, configure, and implement Gemini Enterprise solutions for clients.
• Develop AI agent workflows supporting business use cases and automation.
• Create prototypes and PoCs that evolve to production-ready solutions.
• Architect AI services using Vertex AI, Gemini Enterprise, and related tools.
• Build and deploy LLM-powered apps and enterprise AI integrations.
• Evaluate models, agent patterns, grounding, and integration paths for client use cases.
• Configure Gemini Enterprise agents, integrations, and Google Cloud AI services.
• Collaborate with clients to gather requirements and translate to architecture plans.
• Develop scripts, connectors, or lightweight apps to support agent implementations.
• Support evaluation, testing, and production readiness; ensure cloud security and governance.

Skills

Cloud architecture

AI/ML solution design

Client-facing delivery

Programming & prototyping

GCP expertise

Gemini Enterprise

Agent-based AI workflows

Security & IAM

Communication skills

Education

Bachelor's degree in CS/Engineering/related

Tools

Vertex AI

Gemini Enterprise

Gemini

BigQuery

Cloud Functions

Cloud Run

APIs

Job description

Google Cloud AI Solutions Architect, Gemini Enterprise

Overview

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.

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.
• Google Cloud Professional Cloud Architect or Google Cloud Professional Machine Learning Engineer certification.
  
• 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.

Preferred Skills

• Google Cloud Generative AI Leader 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.

Additional Information

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.