Python Backend Engineer

Job Summary We are seeking an experienced Python Developer with a strong background in designing, developing, and deploying scalable applications. The ideal candidate should have hands-on experience with AWS cloud services and a solid understanding of AI integration , including working with AI/ML models, APIs, or Generative AI solutions. This role requires strong problem-solving skills, expertise in backend development, and the ability to build secure, high-performance applications. Key Responsibilities Design, develop, test, and maintain scalable Python applications and APIs. Develop backend services using Python frameworks such as FastAPI, Flask, or Django . Build and integrate RESTful APIs and microservices. Deploy, manage, and optimize applications on AWS Cloud . Integrate AI/ML and Generative AI capabilities into applications using APIs and cloud AI services. Work with databases such as PostgreSQL, MySQL, MongoDB, or DynamoDB. Implement secure, scalable, and high-performance software solutions. Collaborate with cross-functional teams to define, design, and deliver new features. Troubleshoot production issues and optimize application performance. Follow best practices for code quality, testing, CI/CD, and documentation. Required Skills 5+ years of experience in Python development. Strong expertise in Python 3.x . Experience with FastAPI, Flask, or Django . Strong understanding of REST APIs and Microservices architecture. Hands-on experience with AWS services such as: EC2 Lambda S3 API Gateway RDS DynamoDB IAM CloudWatch ECS/EKS (preferred) Experience with SQL and NoSQL databases. Familiarity with Docker and Kubernetes is an advantage. Experience with Git and CI/CD pipelines. Strong debugging and analytical skills. Preferred Skills Experience integrating AI/ML or Generative AI solutions into enterprise applications. Hands-on experience with OpenAI APIs, Amazon Bedrock, AWS SageMaker, Anthropic Claude, Google Vertex AI, or Azure OpenAI . Knowledge of LangChain, LangGraph, LlamaIndex, RAG (Retrieval-Augmented Generation), vector databases (Pinecone, ChromaDB, FAISS), and prompt engineering . Experience with asynchronous programming and event-driven architectures. Familiarity with Infrastructure as Code (Terraform or AWS CloudFormation). Exposure to MLOps concepts and AI application deployment.