Google Cloud AI Solutions Architect, Gemini Enterprise

🕒 Julho 29

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

💻 Engenheiro de Soluções

👻 Score fantasma 33%

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The Data Sherpas

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2010

💼 Consultoria

🤖 Inteligência Artificial

📣 Marketing

Consulting • Artificial Intelligence • Marketing

A The Data Sherpas é uma empresa de serviços de dados e análises independente de plataforma que ajuda organizações a adotarem soluções de IA, cloud, martech e adtech. Focada em inovação, ela oferece serviços de consultoria e gerenciados para capacitar empresas com capacidades avançadas de dados, IA e cloud, visando decisões estratégicas, eficiência operacional e vantagem competitiva. Seu site enfatiza estudos de caso, parcerias de marca e serviços que abrangem dados, IA, cloud, martech e adtech.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• Must be a U.S. Citizen