Google Cloud AI Solutions Architect, Gemini Enterprise

🕒 July 29

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

💻 Solutions Engineer

👻 Ghost score 21%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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The Data Sherpas

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2010

💼 Consulting

🤖 Artificial Intelligence

📣 Marketing

Consulting • Artificial Intelligence • Marketing

The Data Sherpas is a platform-agnostic data and analytics services firm that helps organizations adopt AI, cloud, martech and adtech solutions. Innovation-focused, they provide consulting and managed services to empower businesses with advanced data, AI and cloud capabilities for strategic decision-making, operational efficiency and competitive advantage. Their website emphasizes case studies, brand partnerships, and services spanning data, AI, cloud, martech and adtech.

📋 Description

• 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.

🎯 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. • 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.

🏖️ Benefits

• Must be a U.S. Citizen