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# Software Engineer (Cloud / AI Platform)

- **Company:** Bayside Solutions
- **Location:** Cupertino, CA, United States (Remote available)
- **Salary:** $104,000.0 - $124,800.0
- **Contract:** Contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Engineering, Distributed Systems, Fault Tolerance, Python (Programming Language), Machine Learning, Service-Oriented Architecture, Systems Architecture, Workflow Management Systems, Data Logging, Feature Store, Google Cloud, Cloud Platform System, Feature Engineering, Data Ingestion, Flask (Web Framework), Software Application Programming, Backend, Fastapi, Containerization, AI Platforms, Kubernetes, Azure AKS, Machine Learning Operations, Asynchronous Programming, Api Design, Grpc, Data Pipelines, Docker, Microservices
- **Published:** November 3, 2026
- **Apply:** https://www.dice.com/job-detail/98ea5c52-3966-4eab-a0ae-c3ce39d5e2a7

## About the Role

* Strong software engineering fundamentals with experience building production backend systems.
 * Strong Python development experience.
 * Experience designing scalable, maintainable, and testable software.
 * Experience building APIs using FastAPI, Flask, gRPC, or similar frameworks.
 * Experience with asynchronous programming and modern backend development practices.
 * Experience building or supporting workflow orchestration systems.
 * Solid understanding of workflow scheduling, task dependencies, retries, and pipeline monitoring.
 * Experience with Apache Airflow or similar orchestration platforms.
 * Experience working with data or machine learning pipelines.
 * Understanding of the machine learning lifecycle, including data ingestion, transformation, feature engineering, model training, evaluation, deployment, and monitoring.
 * Experience enabling machine learning workflows rather than building machine learning models.
 * Experience deploying and operating applications in Kubernetes environments.
 * Good understanding of pods, deployments, services, ConfigMaps, Secrets, ingress, rolling deployments, and autoscaling.
 * Experience with any managed Kubernetes platform such as Amazon EKS, Google Kubernetes Engine, Azure Kubernetes Service, Alibaba ACK, or similar.
 * Understanding of distributed system design, service architecture, scalability, resiliency, asynchronous processing, and fault tolerance.
 * Experience developing applications in AWS, Google Cloud Platform, Azure, or similar cloud environments., * Apache Airflow
 * Flyte or Argo Workflows
 * Docker and containerized applications
 * Microservices architecture
 * CI/CD pipelines
 * Infrastructure as Code
 * Observability, monitoring, and logging platforms
 * Experience supporting AI or machine learning platform engineering
 * Experience with feature stores, model registries, or model serving platforms

## Description

* Design, build, and maintain scalable backend services and APIs using Python.
 * Develop workflow orchestration services that support data ingestion, transformation, machine learning training, evaluation, deployment, and monitoring.
 * Build reusable platform services that enable engineering teams to create and manage end-to-end AI and data pipelines.
 * Design and implement REST and gRPC APIs for internal platform services.
 * Deploy and operate applications in Kubernetes environments.
 * Design reliable, scalable, and highly available distributed systems.
 * Collaborate with platform, infrastructure, data engineering, and machine learning teams to deliver platform capabilities.
 * Troubleshoot production issues across applications, orchestration pipelines, and Kubernetes infrastructure.
 * Contribute to system architecture, technical design, and engineering best practices.
 * Improve platform performance, scalability, reliability, and operational excellence.