Backend Software Engineer - Python & Pipeline Orchestration (Cloud / AI Platform)

W2 ContractPay Rate: $55 - $65 per hourLocation: Cupertino, CA - Remote RoleJob SummaryWe are seeking a highly skilled Backend Software Engineer to join our platform engineering team focused on building scalable data and machine learning pipeline orchestration services within our internal cloud ecosystem. This role sits at the intersection of backend engineering, data platforms, and infrastructure, enabling teams to develop, deploy, and manage end-to-end pipelines across a multi-cloud environment.Duties and ResponsibilitiesDesign, build, and maintain backend services and APIs for pipeline orchestration using PythonDevelop and manage end-to-end workflows for data ingestion, data processing and transformation, machine learning training and evaluation, and model deployment and lifecycle managementBuild scalable and reliable orchestration systems that integrate with internal data and AI platforms.Collaborate with cross-functional teams to enable seamless pipeline execution across services.Ensure system performance, scalability, and reliability in a distributed, multi-cloud environment (AWS, GCP)Troubleshoot production issues across application, pipeline, and infrastructure layersContribute to system design and architecture decisions for next-generation AI and data platforms.Requirements and QualificationsStrong backend engineering experience with Python (required)Experience building APIs and services using frameworks such as Flask, FastAPI, or gRPCHands-on experience working with data pipelines or machine learning pipelinesSolid understanding of Workflow orchestration concepts, distributed systems, and API design and service architectureFamiliarity with Kubernetes and containerized environmentsBasic understanding of pods, deployments, and servicesExperience deploying or operating applications in Kubernetes environmentsExperience working in cloud environments (AWS, GCP, or similar)Preferred QualificationsExperience with orchestration tools such as Apache Airflow or FlyteExposure to ML lifecycle workflows (training, evaluation, deployment)Experience with multi-cloud or hybrid cloud architecturesFamiliarity with data platforms, feature stores, or model serving systemsStrong debugging and troubleshooting skills across logs, monitoring, and distributed systemsBayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.Bayside Solutions, Inc. may collect your personal information during the position application process. Please reference Bayside Solutions, Inc.'s CCPA Privacy Policy at