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Entry Level Kubernetes Developer Jobs (NOW HIRING)

BlackSpade

Software Engineer with DevOps

Atlanta, GA · On-site

$110K/yr

AI & DevOps Engineer (Elite Entry-Level Track) Salary: $70,000/year W2 with a guaranteed ... Master Kubernetes, AWS, and Agentic AI workflows. Elite Mentorship: Continuous 1-on-1 support from ...

BlackSpade

Software Engineer with DevOps

Chicago, IL · On-site

$110K/yr

AI & DevOps Engineer (Elite Entry-Level Track) Salary: $70,000/year W2 with a guaranteed ... Master Kubernetes, AWS, and Agentic AI workflows. Elite Mentorship: Continuous 1-on-1 support from ...

Anthem Engineering

DevOps Engineer

Chantilly, VA · On-site

$54 - $74/hr

Experience with containerization technologies such as Docker and Kubernetes * Experience delivering ... Experience developing in an Agile environment Level: Entry Level - SME Clearance: Active security ...

Anthem Engineering

DevOps Engineer

Chantilly, VA

$54 - $74/hr

Experience with containerization technologies such as Docker and Kubernetes * Experience delivering ... Experience developing in an Agile environment Level: Entry Level - SME Clearance: Active security ...

Anthem Engineering

DevOps Engineer

Chantilly, VA · On-site

$54 - $74/hr

Experience with containerization technologies such as Docker and Kubernetes * Experience delivering ... Experience developing in an Agile environment Level: Entry Level - SME Clearance: Active security ...

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Software Engineer - AI & Edge Kubernetes Orchestration

ZEDEDA

San Jose, CA • On-site

Full-time

Re-posted yesterday

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.

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