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Remote Cloud Support Jobs in Riverside, CA (NOW HIRING)

Tunabear

Senior AWS Developer

Riverside, CA · Remote

Remote Work Hours : 8AM-5PM Pacific Standard Time Responsibilities * Design, develop, deploy, and ... cloud and serverless best practices. * Participate in CI/CD pipeline development and support ...

Ingram Micro

Sr. Software Engineer

Irvine, CA · On-site +1

$112K - $190K/yr

... remote. As a Sr. Software Engineer, you will lead the design, stabilization, and delivery of ... to support multi-tenant architecture and seamless customer adoption. * Leverage Azure Cloud ...

Hyundai Capital

Sr. Salesforce UI/UX Developer

Irvine, CA · On-site +1

$59.50 - $79/hr

Automotive Finance / Industry Cloud Solution Delivery * Deliver Salesforce solutions supporting ... Hybrid flexibility - 4 days in office, 1 day remote * Vehicle perks - monthly vehicle allowance ...

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All JobsCloud Support JobsRemote Cloud Support JobsRemote Cloud Support Jobs in Riverside, CA

Remote Cloud Support information

See Riverside, CA salary details

$24

$65

$91

How much do remote cloud support jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for remote cloud support in Riverside, CA is $65.61, according to ZipRecruiter salary data. Most workers in this role earn between $55.91 and $74.71 per hour, depending on experience, location, and employer.

What is a remote cloud support?

A Remote Cloud Support job involves assisting customers or clients with issues related to cloud-based services and infrastructure, all while working from a remote location. Professionals in this role troubleshoot technical problems, provide guidance on cloud tools, and help manage cloud resources such as servers, storage, and applications. They often interact with customers via email, chat, or phone, and may also work with various cloud platforms like AWS, Azure, or Google Cloud. Strong communication and problem-solving skills are essential, along with a solid understanding of cloud technologies.

What are the key skills and qualifications needed to thrive as a remote cloud support?

To thrive as a Remote Cloud Support specialist, you need a solid understanding of cloud computing platforms (such as AWS, Azure, or Google Cloud), networking, troubleshooting, and often a degree in computer science or a related field. Familiarity with cloud management tools, ticketing systems, and relevant certifications like AWS Certified Solutions Architect or CompTIA Cloud+ is typically required. Excellent problem-solving, communication, and customer service skills help you address client issues efficiently and maintain strong relationships. These skills ensure effective resolution of technical challenges, high customer satisfaction, and reliable cloud service delivery in a remote work environment.

What are some common challenges faced by remote cloud support, and how can they be managed?

Remote Cloud Support professionals often encounter challenges such as troubleshooting complex cloud infrastructure issues without direct, on-site access and collaborating across time zones with global teams. To manage these, strong communication skills and proficiency with remote diagnostic tools are essential. Staying updated with evolving cloud technologies and practicing proactive problem-solving can also help in addressing technical issues efficiently. Building good relationships with both clients and internal teams ensures smoother collaboration and more effective support.

What is the difference between Remote Cloud Support vs Remote Cloud Engineer?

AspectRemote Cloud SupportRemote Cloud Engineer
CertificationsCloud certifications (e.g., AWS, Azure) often preferredSimilar certifications, with additional focus on architecture and development
Work EnvironmentCustomer support, troubleshooting, and issue resolutionDesigning, deploying, and maintaining cloud infrastructure
Employer & Industry UsageIT service providers, cloud service companiesTech companies, cloud service providers, enterprise IT teams
Search & Comparison IntentUnderstanding support roles in cloud servicesExploring cloud infrastructure development and deployment

Remote Cloud Support focuses on assisting clients with troubleshooting and resolving cloud-related issues, often in a customer support capacity. Remote Cloud Engineers design, implement, and maintain cloud infrastructure, requiring more technical expertise. While both roles involve cloud platforms and certifications, their core responsibilities and work environments differ significantly.

What are popular job titles related to Remote Cloud Support jobs in Riverside, CA?

For Remote Cloud Support jobs in Riverside, CA, the most frequently searched job titles are:

What job categories do people searching Remote Cloud Support jobs in Riverside, CA look for?

The top searched job categories for Remote Cloud Support jobs in Riverside, CA are:

What cities near Riverside, CA are hiring for Remote Cloud Support jobs?

Cities near Riverside, CA with the most Remote Cloud Support job openings:

Remote Cloud Support jobs near you
Infographic showing various Remote Cloud Support job openings in Riverside, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 20% Part Time, and 6% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $136,462 per year, or $65.6 per hour.

Generative AI Senior Developer - Google Cloud (Contract to Hire) - Hybrid Remote - Western States Re

e360

Irvine, CA • On-site, Remote

$80 - $90/hr

Contractor

Re-posted 2 days ago

Job description

Rate: $80 - $90/ hour (Depending on Experience)
Note: MUST be US Citizen or Green Card Holder
***NO RECRUITING AGENCIES***
***NO C2C***
***NO Sponsorship available***
About e360's App Engineering
e360 is a 30+ year privately-owned company with a focus on our people, our clients and leading technologies. e360's Cloud Services Division is a rapidly growing business helping clients manage their Cloud technology. Our team is comprised of leaders that focus on delivering innovative consulting solutions that leverage leading and emerging technologies.
We are a dynamic and entrepreneurial consulting company that offers ample opportunities for professional development and growth suited to each individual's personal and professional goals. We offer internal, and subsidize external, trainings, and reimburse the cost of technology certification exams and / or renewals. Our family-founded business sees work life fit as a core value that all of our practitioners practice - the value you add to your team is more important than the time that you 'clock in and out.' You will have numerous opportunities to interface with senior leadership, and benefit from mentorship internally or through introductions through external networks to support your growth.
Description
The Advanced Generative AI Developer is a hands-on consultant responsible for designing, building, and deploying production-ready Generative AI and agentic solutions on Google Cloud.
This role requires strong Python and cloud development experience, practical knowledge of Google Agent Development Kit, Gemini, Vertex AI, and GCP-native application and data services. The consultant will work directly with client and project teams to translate business requirements into secure, scalable, and maintainable AI solutions.
What You'll Do
  • Design, build, test, and deploy Generative AI applications and intelligent agents on Google Cloud.
  • Develop single-agent and multi-agent solutions using Google Agent Development Kit.
  • Integrate Gemini models with enterprise APIs, databases, applications, and business workflows.
  • Deploy AI applications using Agent Engine, Cloud Run, GKE, or other appropriate GCP services.
  • Build Retrieval-Augmented Generation solutions using services such as BigQuery, Vertex AI Vector Search, Cloud Storage, and Document AI.
  • Develop APIs, microservices, agent tools, MCP integrations, and event-driven workflows.
  • Build data pipelines to ingest, transform, chunk, embed, index, and retrieve structured and unstructured data.
  • Implement session management, memory, tool calling, human approval, and agent orchestration patterns.
  • Apply automated testing, CI/CD, logging, monitoring, tracing, evaluation, and cost-management practices.
  • Implement Google Cloud security using IAM, service accounts, Workload Identity Federation, Secret Manager, and private networking.
  • Troubleshoot issues across agents, models, APIs, data pipelines, integrations, security, and cloud deployments.
  • Create architecture diagrams, technical designs, API specifications, deployment guides, and operational documentation.
  • Own technical workstreams and provide design reviews, code reviews, and guidance to other developers.
  • Participate in client discovery, architecture, testing, deployment, and knowledge-transfer activities.

Requirements
  • Significant experience developing and deploying applications on Google Cloud.
  • Advanced Python development experience.
  • Hands-on experience building Generative AI or agentic applications.
  • Experience with Google Agent Development Kit, including agents, tools, workflows, sessions, state, and multi-agent patterns.
  • Experience integrating Gemini models using Vertex AI or Google Gen AI SDKs.
  • Experience with Agent Engine, Cloud Run, GKE, Cloud Functions, or similar GCP runtimes.
  • Experience designing and implementing RAG solutions.
  • Experience with BigQuery and Google Cloud data services.
  • Experience building APIs using frameworks such as FastAPI.
  • Experience with REST APIs, asynchronous processing, event-driven architecture, and microservices.
  • Understanding of MCP and its use in connecting agents to enterprise tools and systems.
  • Experience with SQL, document stores, object storage, embeddings, semantic search, or vector databases.
  • Experience with Git, automated testing, CI/CD, Docker, and infrastructure as code.
  • Understanding of Google Cloud IAM, service accounts, Secret Manager, networking, logging, and monitoring.
  • Ability to evaluate tradeoffs involving model quality, latency, security, scalability, reliability, and cost.

Candidates are not expected to have experience with every listed GCP service. However, they must have hands-on experience delivering Generative AI solutions and be able to explain their architecture and implementation decisions.
Preferred Qualifications
  • Experience delivering client-facing Google Cloud consulting projects.
  • Experience leading a technical workstream from discovery through production deployment.
  • Experience deploying ADK agents using Agent Engine, Cloud Run, or GKE.
  • Experience implementing MCP servers, custom agent tools, or enterprise integrations.
  • Experience with Vertex AI Vector Search, BigQuery Vector Search, Document AI, Apigee, Pub/Sub, Eventarc, or Workflows.
  • Experience with Terraform, Cloud Build, Artifact Registry, and automated GCP deployment pipelines.
  • Experience implementing AI evaluation, agent testing, observability, guardrails, and cost monitoring.
  • Relevant Google Cloud certifications.

Professional Skills
  • Strong consulting, communication, and problem-solving skills.
  • Ability to translate business requirements into practical technical solutions.
  • Ability to explain complex AI and cloud concepts to technical and non-technical stakeholders.
  • Strong documentation and technical leadership skills.
  • Ability to work independently and manage changing project priorities.
  • Ability to identify and communicate technical risks, dependencies, and blockers.
  • Willingness to mentor other developers and contribute to reusable delivery standards.

Critical Success Factors
  • Ability to independently design and deliver production-ready AI solutions on Google Cloud.
  • Strong practical knowledge of Google ADK, Gemini, Vertex AI, and GCP architecture.
  • Ability to build agents that securely interact with APIs, data, tools, and enterprise systems.
  • Ability to determine when to use agentic, deterministic, serverless, containerized, or managed-service patterns.
  • Commitment to security, testing, observability, governance, maintainability, and cost control.
  • Ability to own technical workstreams and consistently deliver high-quality client outcomes.

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