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Remote Google Cloud Platform Jobs in Riverside, CA

Shield

Service Desk Manager - Tier II

Anaheim, CA · On-site +1

$93K - $108K/yr

Strong technical background in Windows Server (2016/2019/2022), networking (Cisco, Sophos, SonicWall), cloud platforms (Microsoft 365, Google Workspace, Azure AD), and remote troubleshooting.

MongoDB

Senior Python Engineer

Ontario, CA · On-site +1

$123K - $166K/yr

Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud data platform and is available across AWS, Google Cloud, and Microsoft Azure. With offices worldwide and over ...

NextDeavor Inc.

Mid Level Software Engineer

Irvine, CA · Remote

$100K - $115K/yr

Mid Level Software Engineer Full-time Remote Exclusive confidential search -- details shared with ... Experience with Docker, CI/CD pipelines, and cloud platforms (Azure, AWS) * Experience with AI ...

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See Riverside, CA salary details

$11

$64

$88

How much do remote google cloud platform jobs pay per hour?

As of Aug 8, 2026, the average hourly pay for remote google cloud platform in Riverside, CA is $64.38, according to ZipRecruiter salary data. Most workers in this role earn between $56.44 and $77.26 per hour, depending on experience, location, and employer.

What skills and qualifications are needed to thrive in a remote Google Cloud Platform position?

To excel as a Remote Google Cloud Platform professional, you typically need strong expertise in cloud architecture, infrastructure management, scripting, and experience with Google Cloud Platform (GCP) services. Familiarity with tools such as Kubernetes, Terraform, and CI/CD pipelines, along with certifications like Google Cloud Certified - Professional Cloud Architect, is highly valued. Excellent problem-solving skills, proactive communication, and the ability to work independently in a distributed team environment set top candidates apart. These skills are essential for effectively designing, deploying, and managing scalable cloud solutions while collaborating remotely across diverse teams.

What is a remote Google Cloud Platform?

A Remote Google Cloud Platform (GCP) job involves working with Google Cloud services to develop, manage, and optimize cloud-based solutions from a remote location. Professionals in this field may work as cloud engineers, architects, or DevOps specialists, leveraging GCP tools for computing, storage, networking, and security. These roles typically require expertise in cloud infrastructure, automation, and security best practices. Remote GCP jobs offer flexibility while ensuring businesses can scale their applications efficiently in the cloud.

What are common challenges faced by professionals working remotely with Google Cloud Platform?

Professionals in remote Google Cloud Platform roles often face challenges related to coordinating with geographically dispersed teams and managing complex, large-scale cloud infrastructures with minimal direct supervision. Clear documentation, consistent communication, and strong time management are essential for overcoming these hurdles. Additionally, staying updated with the rapid evolution of GCP services and best practices can be demanding but is critical for delivering robust cloud solutions. Those who thrive in this role are proactive about collaborating through virtual channels and continuously seek to enhance their technical expertise.

What job categories do people searching Remote Google Cloud Platform jobs in Riverside, CA look for? The top searched job categories for Remote Google Cloud Platform jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Remote Google Cloud Platform jobs? Cities near Riverside, CA with the most Remote Google Cloud Platform job openings:
Remote Google Cloud Platform jobs near you
Infographic showing various Remote Google Cloud Platform job openings in Riverside, CA as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% Remote job distribution, with an average salary of $133,919 per year, or $64.4 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

Posted 20 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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