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Associate Google Cloud Ai Jobs (NOW HIRING)

Devoteam

Google Cloud AI Engineer

Alexis, NC

$52.25 - $69.75/hr

Responsabilidades * Disenar, desarrollar e implementar agentes conversacionales inteligentes utilizando Vertex AI Agent Builder. * Integrar LLMs de Google Cloud y de terceros en agentes ...

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Associate Google Cloud Ai information

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How much do associate google cloud ai jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for associate google cloud ai in the United States is $18.76, according to ZipRecruiter salary data. Most workers in this role earn between $15.38 and $21.15 per hour, depending on experience, location, and employer.

What is the difference between Associate Google Cloud Ai vs Data Analyst?

AspectAssociate Google Cloud AiData Analyst
Required CredentialsGoogle Cloud certifications, basic programming skillsData analysis certifications, SQL, Excel skills
Work EnvironmentCloud platforms, AI/ML projectsData collection, analysis, reporting
Industry UsageTech, AI, cloud servicesBusiness, finance, marketing

Associate Google Cloud Ai professionals focus on implementing AI solutions on Google Cloud, requiring cloud certifications and technical skills. Data Analysts interpret data to inform business decisions, emphasizing data tools and analysis. While both roles involve data and technical knowledge, their core functions and work environments differ significantly.

What cities are hiring for Associate Google Cloud Ai jobs? Cities with the most Associate Google Cloud Ai job openings:
What are the most commonly searched types of Google Cloud Ai jobs? The most popular types of Google Cloud Ai jobs are:
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Associate Google Cloud Ai jobs near you

Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas

Atlanta, GA • On-site

$61 - $83.75/hr

Full-time

Re-posted 13 days ago

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.

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