Zededa

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

San Jose, CA · Contract

No sponsorship$120k-$140kDetected 23 days ago

GitAWSAzureKubernetesHelmCI/CDGitHub ActionsJenkinsCircleCILinuxRESTKafkaOAuthMachine LearningDeep LearningPyTorchNLPLangGraphA/B TestingAdaptability

About the role

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.
This is a hybrid role requiring three days per week onsite at our San Jose office.

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.
Participate in design discussions, write clean code, submit pull requests, and iterate rapidly based on feedback.
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.

Required: Bachelor's or Master's degree in Computer Science, AI/ML, or a related technical field - or equivalent practical experience.
Experience with AI agent frameworks: LangChain, LangGraph, LangFuse, or similar.
Experience with CI/CD systems: Jenkins, CircleCI, GitHub Actions, or similar.
Familiarity with AWS or Azure tooling.
Knowledge of cloud-native
Knowledge of cloud-native technologies: Kafka, REST APIs, SSO/OAuth, microservices patterns.
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 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.
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.
Hands-on experience with
Preferred: Hands-on experience with Kubernetes advanced constructs: Custom Resource Definitions (CRDs), Operators, Controllers, and the kubeconfig API.

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 ArgoCD or other GitOps-based continuous delivery tools for Kubernetes.
Base pay is determined by considering your skills, qualifications, experience, and location.

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.

This listing is sourced directly from Zededa's careers page and normalized into a canonical job model.