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Entry Level Cloud Computing Jobs in California (NOW HIRING)

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How much do entry level cloud computing jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for entry level cloud computing in California is $62.06, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $70.67 per hour, depending on experience, location, and employer.

What is an entry level cloud computing?

An entry-level cloud computing job involves working with cloud technologies to manage, deploy, and troubleshoot cloud-based applications and infrastructure. Common roles include Cloud Support Associate, Junior Cloud Engineer, and Cloud Administrator. Responsibilities often include configuring cloud services, monitoring performance, and ensuring security compliance. Employers typically look for knowledge of platforms like AWS, Azure, or Google Cloud and familiarity with networking, operating systems, and scripting languages. Certifications such as AWS Certified Cloud Practitioner or Microsoft Azure Fundamentals can help candidates stand out.

What types of projects or tasks are typically assigned to entry level cloud computing professionals?

Entry level cloud computing professionals usually support team members by assisting with cloud infrastructure setup, managing resources, monitoring system performance, and troubleshooting basic issues. They may help automate routine tasks, maintain documentation, and collaborate with developers or IT staff on deployments and updates. Projects often involve learning company-specific systems and best practices, working with cloud management consoles, and gaining hands-on experience with different cloud services. This role offers a great opportunity to build foundational skills while contributing to real business needs and learning directly from experienced cloud engineers.

What are the key skills and qualifications needed to thrive in entry level cloud computing, and why are they important?

To thrive in an Entry Level Cloud Computing role, a foundational understanding of cloud platforms (such as AWS, Azure, or Google Cloud), networking basics, and some programming or scripting knowledge is essential—often supported by a degree in computer science or a related field. Familiarity with tools like Amazon EC2, Kubernetes, and entry-level certifications such as AWS Certified Cloud Practitioner or Microsoft Azure Fundamentals is highly valued. Strong problem-solving skills, eagerness to learn, effective communication, and teamwork enable individuals to excel in collaborative and dynamic environments. These skills are important because they allow employees to adapt to evolving cloud technologies while delivering reliable, scalable solutions in real-world business settings.

What are the most commonly searched types of Cloud Computing jobs in California?

The most popular types of Cloud Computing jobs in California are:

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For Entry Level Cloud Computing jobs in California, the most frequently searched job titles are:

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What cities in California are hiring for Entry Level Cloud Computing jobs?

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Entry Level Cloud Computing jobs near you
Infographic showing various Entry Level Cloud Computing job openings in California as of September 2026, with employment types broken down into 78% Full Time, 13% Part Time, and 9% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,089 per year, or $62.1 per hour.

Software Engineer - AI & Edge Kubernetes Orchestration - San Jose, CA

San Jose, CA • On-site

Zededa
Software Development • 11 - 50 employees
Learn more about Zededaexternal

Temporary

Re-posted 20 days ago

Key responsibilities

  • Design, develop, and maintain software components that connect AI model lifecycle management with Kubernetes-based edge orchestration.

  • Build and extend Kubernetes controllers, operators, and Custom Resource Definitions (CRDs) to support AI workload scheduling and deployment at the edge.

  • Write and maintain Helm charts for deploying services into Kubernetes clusters.

Job description

About ZEDEDA
ZEDEDA unlocks the value of AI where it matters most, enabling enterprises to create, secure and operate edge AI at scale. ZEDEDA's Edge Intelligence products and solutions are used by global distributed enterprises to rapidly realize and deploy autonomous intelligence wherever they operate, turning real-time data into real and tangible business outcomes and decisions. Trusted by the world's largest organizations, ZEDEDA is backed by world-class investors, with teams in the United States, Germany, India, and the United Arab Emirates. For more information, visit www.ZEDEDA.ai.
Location: San Jose, CA (3 days onsite)
This is an onsite position based in our San Jose, CA office. Candidates must be able to reliably commute to this location; relocation assistance and travel/commuting expenses are not provided.
Role Summary
This position is not eligible for visa sponsorship. Applicants must be authorized to work in the United States without employer sponsorship, now and in the future. We're looking for a curious, self-driven entry level Software Engineer who sits at the intersection of AI and cloud-native infrastructure. You'll work alongside experienced engineers on real-world problems in edge orchestration - problems that are often loosely defined, fast-moving, and require you to think from first principles. You bring energy, adaptability, and a genuine enthusiasm for using AI tools and technologies, both as the subject of your work and as instruments in how you work every day.
This role for a recent graduate or someone with up to two years of industry experience. You won't be handed a perfectly scoped ticket - you'll be trusted to figure things out.
Core Responsibilities:
  • Design, develop, and maintain software components that bridge AI model lifecycle management with Kubernetes-based edge orchestration.
  • Build and extend Kubernetes controllers, operators, and Custom Resource Definitions (CRDs) to support AI workload scheduling and deployment at the edge.
  • Work with ONNX, GenAI, and ML models - integrating them into production-ready pipelines and edge environments.
  • Use AI coding agents (Claude Code, Copilot, Codex, etc.) as first-class tools in your daily development workflow.
  • Participate in design discussions, write clean code, submit pull requests, and iterate rapidly based on feedback.
  • Contribute to open-source components related to ZEDEDA's platform and the broader cloud-native ecosystem.
  • Write and maintain Helm charts for deploying services into Kubernetes clusters.
  • Collaborate with cross-functional teams across AI, infrastructure, and product to ship features end-to-end.

Qualifications:
Required:
  • Bachelor's or Master's degree in Computer Science, AI/ML, or a related technical field - or equivalent practical experience.
  • Foundational knowledge of machine learning concepts: neural networks, deep learning, model training and inference, and attention mechanisms (self-attention / transformers).
  • Familiarity with ONNX models, GenAI model architectures, or frameworks like PyTorch or TensorFlow.
  • Practical exposure to Kubernetes - understanding of pods, deployments, services, namespaces, and controllers. Familiarity with lightweight Kubernetes distributions such as k3s is a plus, particularly in the context of resource-constrained edge environments.
  • Comfort working with Git, submitting pull requests, reading diffs, and collaborating in a version-controlled environment.
  • Ability to work with vague or evolving problem statements and drive toward clarity independently.
  • Language-agnostic development mindset - you pick the right tool for the job and learn what you don't know.
  • Comfortable with basic Linux commands and shell scripting.

Preferred:
  • Hands-on experience with Kubernetes advanced constructs: Custom Resource Definitions (CRDs), Operators, Controllers, and the kubeconfig API.
  • CKA (Certified Kubernetes Administrator) or CKD certification, or active preparation for it.
  • Experience with AI agent frameworks: LangChain, LangGraph, LangFuse, or similar.
  • Demonstrated use of AI coding tools (Claude Code, GitHub Copilot, OpenAI Codex) in real development workflows - not just familiarity, but fluency.
  • Prior contribution to, or porting of, open-source projects.
  • Experience with CI/CD systems: Jenkins, CircleCI, GitHub Actions, or similar.
  • Familiarity with AWS or Azure tooling.
  • Knowledge of cloud-native technologies: Kafka, REST APIs, SSO/OAuth, microservices patterns.
  • Exposure to Helm chart authoring, not just usage.
  • Awareness of edge computing concepts, IoT, or distributed systems.
  • Familiarity with edge AI hardware platforms and inference infrastructure: NVIDIA Jetson (Jetpack SDK), Qualcomm IQ9, NVIDIA Triton Inference Server, vLLM, or similar model serving frameworks.
  • Familiarity with ArgoCD or other GitOps-based continuous delivery tools for Kubernetes.

Pay & Benefits
At ZEDEDA, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. Base pay is determined by considering your skills, qualifications, experience, and location. For this role the base pay range is $120,000-$140,000
Why ZEDEDA
ZEDEDA offers competitive salary, performance-based bonuses, comprehensive medical benefits, hybrid work flexibility, and meaningful opportunities for technical growth and advancement. Engineers at every level have access to AI productivity tools, on the job learning, and a culture that celebrates curiosity and experimentation - because at ZEDEDA, impact matters more than activity, and learning is never optional.

Apply