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

Descrição da Vaga

Requisitos

• Strong backend engineering experience with Python (required)
• Experience building APIs and services using frameworks such as Flask, FastAPI, or gRPC
• Hands-on experience working with data pipelines or machine learning pipelines
• Solid understanding of Workflow orchestration concepts, distributed systems, and API design and service architecture
• Familiarity with Kubernetes and containerized environments:
• Basic understanding of pods, deployments, and services
• Experience deploying or operating applications in Kubernetes environments
• Experience working in cloud environments (AWS, GCP, or similar)
• Python, Backend Engineering, API Development, Flask, FastAPI, gRPC, Data Pipelines, Machine Learning Pipelines, Workflow Orchestration, Pipeline Orchestration, Distributed Systems, System Design, Service Architecture, Kubernetes, Containerization, Pods and Deployments, Cloud Computing, AWS, GCP, Multi-Cloud Architecture, Data Ingestion, Data Processing, Data Transformation, Machine Learning Training, Model Evaluation, Model Deployment, ML Lifecycle Management, Apache Airflow, Flyte, Data Platforms, Feature Stores, Model Serving, Performance Optimization, Scalability, Reliability Engineering, Troubleshooting, Debugging, Monitoring, Cross-Functional Collaboration

Responsabilidades

• 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
• Design, build, and maintain backend services and APIs for pipeline orchestration using Python
• Develop and manage end-to-end workflows for data ingestion, data processing and transformation, machine learning training and evaluation, and model deployment and lifecycle management
• Build 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 layers
• Contribute to system design and architecture decisions for next-generation AI and data platforms

Benefícios