Python Developer | Remote (In-person interview to Dallas, TX is must) | W2 Only
About the Position Key Responsibilities: Design, develop, and maintain scalable backend services using Python and FastAPI Build and optimize RESTful APIs for performance, reliability, and scalability Develop and manage distributed systems using GKE and serverless architectures Implement messaging solutions using Pub/Sub patterns Work with relational and non-relational databases for efficient data storage and retrieval Optimize application performance using caching mechanisms like Redis and parallel processing Integrate AI/LLM capabilities into backend services where applicable Write clean, testable, and maintainable code following best practices Perform unit, integration, and regression testing with automation frameworks Collaborate with cross-functional teams and participate in code reviews Implement and manage CI/CD pipelines for smooth deployments Troubleshoot, monitor, and improve system performance and reliability Responsibilities
- Design, develop, and maintain scalable backend services using Python and FastAPI
- Build and optimize RESTful APIs for performance, reliability, and scalability
- Develop and manage distributed systems using GKE and serverless architectures
- Implement messaging solutions using Pub/Sub patterns
- Work with relational and non-relational databases for efficient data storage and retrieval
- Optimize application performance using caching mechanisms like Redis and parallel processing
- Integrate AI/LLM capabilities into backend services where applicable
- Write clean, testable, and maintainable code following best practices
- Perform unit, integration, and regression testing with automation frameworks
- Collaborate with cross-functional teams and participate in code reviews
- Implement and manage CI/CD pipelines for smooth deployments
- Troubleshoot, monitor, and improve system performance and reliability Requirements
- Languages & Frameworks: Python, SQL, FastAPI
- API & Backend Development: RESTful API design and implementation; Pub/Sub messaging systems; Distributed systems (GKE, Serverless compute)
- Databases: Relational and NoSQL databases; ORMs
- Performance & Intelligence: Redis; Threading and parallelism; LLM (Large Language Models); AI technologies
- Testing: Unit, regression, and integration testing; Automated testing and mocking frameworks
- DevOps & CI/CD: CI/CD tools and practices; Git; Bash scripting; UNIX utilities and commands
- Cloud Platforms: GCP, AWS, or Azure
- Collaboration & Methodologies: Agile and Waterfall methodologies; Code reviews and cross-functional collaboration
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- Dataflow
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