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Entry Level Gitops Engineer Jobs (NOW HIRING)

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Full-Stack Cloud Engineer

Chicago, IL · On-site

$77K - $202K/yr

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Full-Stack Cloud Engineer

Tampa, FL · On-site

$77K - $202K/yr

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Drive a GitOps promotion path through dev, QA, stage, and prod on a major cloud provider (AWS ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Entry Level Gitops Engineer information

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$30K

$69.4K

$118K

How much do entry level gitops engineer jobs pay per year?

As of Jul 31, 2026, the average yearly pay for entry level gitops engineer in the United States is $69,362.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $78,500.00 per year, depending on experience, location, and employer.

What are some typical challenges faced by entry level GitOps engineers when integrating new applications into an existing CI/CD pipeline?

Entry level GitOps engineers often encounter challenges such as managing diverse application configurations, ensuring consistent deployment workflows, and troubleshooting permissions or access issues within Kubernetes clusters. Collaborating with development and operations teams to align on best practices for version control and automation is also common. Proactively learning the organization's CI/CD tools and automation scripts, as well as seeking feedback from senior engineers, can help overcome these hurdles and build confidence in managing production deployments.

What are the key skills and qualifications needed to thrive as an Entry Level GitOps Engineer, and why are they important?

To thrive as an Entry Level GitOps Engineer, you need foundational knowledge in software development, version control (especially Git), and container orchestration concepts, often supported by a degree in computer science or a related field. Familiarity with CI/CD tools (such as Jenkins or ArgoCD), Kubernetes, and infrastructure-as-code systems is typically required, along with any relevant cloud certifications (like AWS Certified Cloud Practitioner). Strong problem-solving abilities, attention to detail, and effective communication are crucial soft skills for collaborating with teams and troubleshooting infrastructure issues. These skills are important to ensure the reliable automation and deployment of infrastructure changes, which are central to successful GitOps practices.

What is an Entry Level GitOps Engineer?

An Entry Level GitOps Engineer is a technology professional who helps automate and manage infrastructure and application deployments using GitOps principles. GitOps is a way of implementing continuous deployment for cloud-native applications by using Git as the single source of truth for declarative infrastructure and application code. As an entry-level engineer, the role often involves setting up, maintaining, and troubleshooting deployment pipelines, collaborating with developers and operations teams, and learning best practices for infrastructure as code. This job is ideal for those interested in DevOps, cloud computing, and automation. Typically, entry-level GitOps Engineers work under the supervision of senior engineers while gaining practical experience with tools like Kubernetes, ArgoCD, and Flux.
More about Entry Level Gitops Engineer jobs
What are the most commonly searched types of Gitops Engineer jobs? The most popular types of Gitops Engineer jobs are:
What job categories do people searching Entry Level Gitops Engineer jobs look for? The top searched job categories for Entry Level Gitops Engineer jobs are:
Infographic showing various Entry Level Gitops Engineer job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $69,362 per year, or $33.3 per hour.

Software Engineer - AI & Edge Kubernetes Orchestration

ZEDEDA

San Jose, CA • On-site

Full-time

Re-posted 28 days ago


Job description

Job Summary:
ZEDEDA unlocks the value of AI where it matters most, enabling enterprises to create, secure and operate edge AI at scale. The company is seeking a curious, self-driven entry level Software Engineer who will work alongside experienced engineers on real-world problems in edge orchestration, focusing on integrating AI tools and technologies into their daily workflow.
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.
Company:
ZEDEDA is a provider of distributed orchestration and virtualization software for Edge AI Compute. Founded in 2016, the company is headquartered in San Jose, USA, with a team of 51-200 employees. The company is currently Growth Stage.