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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 ...

PGTEK

Lead Cloud AI Engineer

Kansas City, MO · On-site

$120 - $150/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As we expand our Google Cloud and AI practice, we're seeking a Lead Cloud AI Engineer to serve as the senior technical authority for enterprise cloud migration and AI platform modernization ...

West Monroe

Agentic AI Architect-Google Cloud

Boston, MA · On-site

$70.50 - $90/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Agentic AI Architect-Google Cloud West Monroe is seeking an experienced Agentic AI Architect to join our Technology & Experience (TechEx) practice within the Software discipline. This highly client ...

VDart, Inc.

Senior Google Cloud Architect

Milpitas, CA · On-site

$74 - $94.25/hr

AI & Machine Learning Solutions * Architect and deploy AI/ML solutions leveraging Google Cloud AI services. * Design Generative AI, LLM, RAG (Retrieval-Augmented Generation), and intelligent ...

PGTEK

Cloud AI Engineer - TS/SCI clearance - travel role

Tampa, FL · On-site

$105K - $115K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As we continue expanding our Google Cloud and AI practice, we're looking for a Cloud AI Engineer to help lead the migration of mission-critical applications into secure Google Cloud environments.

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How much do google cloud ai jobs pay per hour?

As of Aug 18, 2026, the average hourly pay for google cloud ai in the United States is $61.71, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $74.04 per hour, depending on experience, location, and employer.

What is a Google Cloud AI?

A Google Cloud AI job typically involves designing, developing, and deploying artificial intelligence and machine learning solutions using Google Cloud's AI and ML services. Professionals in this role work with tools like Vertex AI, TensorFlow, and AutoML to build models and integrate them into business applications. Responsibilities may include data preprocessing, model training, performance optimization, and ensuring scalability within cloud environments. These roles can span various industries, offering AI-powered insights and automation to enhance decision-making and efficiency.

What are the typical daily responsibilities of someone working in a Google Cloud AI role?

Professionals in a Google Cloud AI role typically spend their day designing, developing, and deploying machine learning models using GCP tools and services. They collaborate closely with data engineers, product managers, and other stakeholders to define project requirements, preprocess data, and evaluate model performance. The role may also involve troubleshooting production issues, optimizing existing models, and documenting best practices for ongoing projects. These responsibilities offer exposure to a variety of business problems and the chance to innovate with cutting-edge cloud and AI technologies.

What are the key skills and qualifications needed to thrive in the Google Cloud AI position, and why are they important?

To excel in a Google Cloud AI role, candidates generally need a solid background in computer science, proficiency with AI/ML algorithms, and experience working with cloud platforms, particularly Google Cloud Platform (GCP). Essential technical tools include TensorFlow, Python, BigQuery, and obtaining certifications such as the Google Professional Machine Learning Engineer can be highly beneficial. Strong problem-solving skills, effective communication, and collaboration are valued soft skills in this position. These competencies are crucial for designing, deploying, and optimizing AI solutions that address real business challenges while working within dynamic, interdisciplinary teams.

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Google Cloud Ai jobs near you
Infographic showing various Google Cloud Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $128,365 per year, or $61.7 per hour.

Google Cloud AI Solutions Architect, Gemini Enterprise

The Data Sherpas

Atlanta, GA • On-site

$61 - $83.75/hr

Full-time

Re-posted 2 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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