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Part Time Google Cloud Ai Jobs (NOW HIRING)

Bert Black

AI Intern

Little Rock, AR · Hybrid

$12 - $16/hr

Familiarity with Python, SQL, and cloud-based AI services (e.g., OpenAI, Azure, Google Cloud) * Experience or interest in working with APIs to connect data sources and applications * Strong problem ...

Bert Black

AI Intern

Little Rock, AR · On-site

$11/hr

Familiarity with Python, SQL, and cloud-based AI services (e.g., OpenAI, Azure, Google Cloud) * Experience or interest in working with APIs to connect data sources and applications * Strong problem ...

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How much do part time google cloud ai jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for part time google cloud ai in the United States is $62.89, according to ZipRecruiter salary data. Most workers in this role earn between $53.61 and $71.63 per hour, depending on experience, location, and employer.

What is a part time Google Cloud AI?

A Part Time Google Cloud AI job typically involves working with Google's cloud-based artificial intelligence tools and services, such as machine learning models, data analytics, and AI-driven applications. These roles can include tasks like developing, deploying, or maintaining AI solutions on Google Cloud Platform (GCP), often in a support, engineering, or data science capacity. Part-time positions may offer flexible hours and are ideal for students, freelancers, or professionals seeking to expand their expertise in cloud-based AI technologies while managing other commitments.

How does a part time Google Cloud AI specialist typically collaborate with cross-functional teams and stakeholders?

As a part-time Google Cloud AI specialist, you will frequently work alongside data scientists, software engineers, and business stakeholders to implement AI solutions using Google Cloud technologies. Collaboration often involves participating in sprint meetings, clarifying project requirements, and integrating AI models into existing workflows. Since the role is part-time, strong communication and documentation skills are essential to ensure seamless handoffs and project continuity. You'll also leverage tools like Google Meet and shared project boards to stay aligned with team objectives and timelines.

What are the key skills and qualifications needed to thrive as a part time Google Cloud AI professional, and why are they important?

To excel as a Part Time Google Cloud AI professional, you typically need a strong background in computer science, machine learning principles, and experience with cloud platforms, often supported by relevant coursework or certifications. Familiarity with Google Cloud tools like AI Platform, TensorFlow, BigQuery, and APIs, as well as Google Cloud Professional certifications, is highly valued. Strong problem-solving abilities, effective communication, and adaptability help you collaborate on projects and address evolving client or business needs. These skills and qualities ensure you can develop, deploy, and maintain AI solutions efficiently while meeting organizational goals.

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

AspectPart Time Google Cloud AiPart Time Data Analyst
Required CredentialsGoogle Cloud certifications, AI/ML knowledgeData analysis certifications, SQL, Excel skills
Work EnvironmentCloud platforms, remote or hybridOffice or remote, data-focused environment
Industry UsageTech, AI, cloud servicesBusiness, finance, marketing
Search & Comparison IntentUnderstanding AI roles in cloud computingAnalyzing data for insights

Part Time Google Cloud Ai roles focus on developing and deploying AI solutions on cloud platforms, requiring cloud certifications and AI expertise. In contrast, Part Time Data Analyst positions involve interpreting data to inform business decisions, emphasizing data analysis skills. Both roles are often remote and serve different industry needs, but they share a focus on data and technology.

How to get a job in Part Time Google Cloud Ai?

To secure a part-time role in Google Cloud AI, candidates should have a strong understanding of cloud computing, machine learning, and AI tools such as TensorFlow or Google Cloud Platform services. Relevant certifications like Google Cloud Professional Data Engineer or AI Engineer can improve prospects, along with experience in programming languages like Python. Applying through official job portals and demonstrating practical skills in AI projects are essential steps.
More about Part Time Google Cloud Ai jobs

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What states have the most Part Time Google Cloud Ai jobs?

States with the most job openings for Part Time Google Cloud Ai jobs include:

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The top searched job categories for Part Time Google Cloud Ai jobs are:

Part Time Google Cloud Ai jobs near you
Infographic showing various Part Time Google Cloud Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $130,802 per year, or $62.9 per hour.

Technical Advisor - Cloud, Application, Data & AI

Oran Inc

Herndon, VA • Remote

Part-time

Posted 26 days ago

Job description

Position: Technical Advisor
Employment Type: Part-Time / Hourly
Work Location: Remote
Engagement: Hourly / Consulting
Customer Focus: U.S. Federal Government

Position Overview

We are seeking an experienced Technical Advisor to provide part-time, senior-level technical guidance and solutioning support for our internal teams and Federal Government customer engagements.

The Technical Advisor will serve as a trusted technical resource responsible for developing and reviewing technical solutions, architectures, approaches, and responses across Cloud, Application, Data, Artificial Intelligence, Cybersecurity, and other emerging technology areas.

This is an advisory and solutioning-focused role. The ideal candidate should be able to quickly understand customer requirements, translate business and mission needs into practical technical solutions, and help teams develop compelling and technically sound approaches for Federal customers.

Key Responsibilities
  • Serve as an internal technical advisor and subject matter expert for Federal customer opportunities and projects.
  • Develop high-level and detailed technical solutions and solution architectures based on customer requirements.
  • Provide technical expertise across:
    • Cloud: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP)
    • Application Architecture & Modernization
    • Data Engineering, Data Platforms & Analytics
    • Artificial Intelligence (AI), Generative AI (GenAI) & Machine Learning
    • Application Programming Interfaces (APIs) and Microservices
    • Cybersecurity and Zero Trust
    • DevSecOps, Infrastructure as Code (IaC) and Cloud Automation
    • Containers, Kubernetes and Cloud-Native Architecture
    • Data & AI platforms, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and AI-enabled solutions
    • Other emerging and high-growth technologies relevant to Federal IT modernization.
  • Analyze Requests for Information (RFIs), Requests for Proposals (RFPs), Statements of Work (SOWs), Performance Work Statements (PWSs), and Statements of Objectives (SOOs) and translate requirements into technical approaches.
  • Develop technical solution concepts, architecture diagrams, technology stacks, implementation approaches, and solution narratives.
  • Support proposal solutioning, technical writing, and technical reviews.
  • Collaborate with business development, capture, proposal, recruiting, and delivery teams to develop technically competitive solutions.
  • Evaluate emerging technologies and recommend where they can provide value to Federal customers.
  • Review proposed technical approaches for feasibility, scalability, security, cost, and alignment with Federal requirements.
  • Provide technical mentorship and guidance to internal teams.
  • Participate in customer discussions, technical briefings, solution presentations, and architecture reviews when required.
  • Help identify technology partners, platforms, tools, and technical capabilities needed to support customer requirements.
Required Qualifications
  • 10+ years of progressive experience in technology, IT architecture, engineering, consulting, or technical solutioning.
  • Demonstrated experience developing technical solutions and architectures for complex enterprise environments.
  • Strong knowledge of at least two major cloud platforms, preferably AWS, Azure, and/or GCP.
  • Broad understanding of modern Application, Data, Cloud, AI, and Cybersecurity technologies.
  • Experience translating complex technical requirements into clear, actionable solution approaches.
  • Strong technical writing and presentation skills.
  • Experience supporting Federal Government customers, contracts, proposals, or solutioning efforts.
  • Ability to work independently in a part-time advisory capacity and provide expertise when needed.
  • Ability to communicate complex technical concepts effectively to both technical and non-technical stakeholders.
Preferred Qualifications
  • Experience with Federal IT modernization and cloud transformation.
  • Experience with Enterprise Architecture, Cloud Architecture, Solution Architecture, or Technical Architecture.
  • Knowledge of Federal technology and security frameworks such as:
    • National Institute of Standards and Technology (NIST)
    • Federal Risk and Authorization Management Program (FedRAMP)
    • Federal Information Security Modernization Act (FISMA)
    • Zero Trust Architecture
    • NIST Cybersecurity Framework
  • Experience with Artificial Intelligence, Generative AI, Machine Learning, Large Language Models, Retrieval-Augmented Generation, AI Agents, or AI governance.
  • Experience with cloud-native technologies, Kubernetes, containers, Infrastructure as Code, and DevSecOps.
  • Experience supporting Requests for Proposals (RFPs), Requests for Information (RFIs), Sources Sought, and government technical responses.
  • Relevant certifications such as:
    • AWS Certified Solutions Architect
    • Microsoft Certified: Azure Solutions Architect Expert
    • Google Cloud Professional Cloud Architect
    • Certified Information Systems Security Professional (CISSP)
    • Certified Cloud Security Professional (CCSP)
    • TOGAF certification
    • Other relevant cloud, architecture, cybersecurity, data, or AI certifications.
Ideal Candidate

The ideal candidate is a technology generalist with deep expertise in architecture and solutioning rather than someone limited to a single technology stack.

You should be able to walk into a Federal customer requirement, understand the mission and technical challenges, and answer:

“What should we build, how should we build it, what technologies should we use, and why is this the right solution?”

The candidate should be comfortable moving between Cloud + Application + Data + AI + Security + Emerging Technologies and providing practical, commercially viable recommendations.

Engagement Details
  • Part-Time
  • Remote
  • Hourly Consulting Engagement
  • Flexible hours based on project and proposal requirements
  • Primarily internal advisory and Federal customer support
  • Opportunity to support multiple Federal technology initiatives and proposals