Senior Python Backend Engineer

Job Description

Job Overview :

We are seeking an experienced Senior Python Backend Engineer to join our dynamic engineering team. In this role, you will architect, develop, and scale high-performance backend systems. The ideal candidate will have extensive experience building production-grade APIs, managing distributed systems, and implementing robust data processing pipelines with a focus on reliability and scalability.

Key Responsibilities :

Design and develop scalable backend APIs using FastAPI with advanced async / await patterns for high-concurrency applications.

Build and maintain sophisticated distributed task processing systems using Celery, Redis, and RabbitMQ for background job orchestration.

Design and implement RAG (Retrieval Augmented Generation) systems for intelligent document processing and question-answering capabilities.

Integrate and optimize vector databases (Qdrant) for semantic search and similarity matching in large-scale document retrieval systems.

Build and maintain real-time voice processing systems including speech-to-text, text-to-speech, and voice-enabled conversational AI interfaces.

Implement advanced MongoDB operations including complex aggregation pipelines, query optimization, and performance tuning for large-scale data processing.

Develop resilient external API integrations with comprehensive retry logic, rate limiting, and webhook event systems.

Design and implement robust authentication and authorization systems using JWT tokens and role-based access control.

Develop and maintain LangChain-based AI pipelines for document ingestion, text chunking, embedding generation, and retrieval workflows.

Build containerized microservices architecture with Docker and orchestrate multi-service deployments.

Implement comprehensive error handling, monitoring, and observability solutions for production systems and AI model inference endpoints.

Write and maintain technical documentation, conduct code reviews, and mentor junior developers.

Collaborate with DevOps teams on cloud deployment strategies and CI / CD pipeline optimization.

Requirements

Required Skills & Qualifications :

5+ years of professional Python development experience with mastery of async / await patterns and concurrent programming.

Expert-level proficiency in FastAPI framework with experience building complex production APIs, middleware integration, and streaming responses.

Advanced MongoDB expertise including aggregation pipelines, query optimization, schema design, replica sets, and performance tuning.

Proven experience with RAG (Retrieval Augmented Generation) systems and implementing end-to-end document processing pipelines for intelligent search and Q&A applications.

Hands-on experience with vector databases (Qdrant) for semantic search, embedding storage, and similarity matching at scale.

Proficiency with LangChain framework including document loaders, text splitters, embedding models, vector stores, retrievers, and chain orchestration.

Experience with real-time voice APIs and audio processing including OpenAI Realtime API.

Hands-on experience with distributed task processing using Celery, Redis, and message queue systems (RabbitMQ / Redis).

Proven experience integrating external APIs with sophisticated retry mechanisms, rate limiting, exponential backoff, and webhook implementations.

Strong security implementation skills including JWT authentication, API security best practices, input validation, and secure file handling.

Production experience with cloud platforms (Azure / AWS / GCP) including managed services, blob storage, and containerized deployments.

Proficiency with Docker containerization, multi-stage builds, and container orchestration.

Experience with database design, transaction management, connection pooling, and data migration strategies.

Strong understanding of software architecture patterns, dependency injection, and separation of concerns.

Preferred Qualifications :

Knowledge of Azure ecosystem including Blob Storage, managed Redis, Azure Cognitive Services, and Azure-specific deployment patterns.

Experience with OpenAI API integration, prompt engineering, and managing large language model inference at scale.

Knowledge of speech processing technologies including speech-to-text (Whisper, Azure Speech, Google Speech), text-to-speech (ElevenLabs, Azure TTS), and voice activity detection.

Experience with real-time audio streaming protocols, audio format handling (WAV, MP3, WebM), and optimizing voice processing pipelines for low latency.

Familiarity with embedding models (OpenAI, Sentence Transformers) and their optimization for production use cases.

Knowledge of additional AI frameworks and tools such as Hugging Face Transformers, Llama Index, or custom ML pipeline development.

Familiarity with monitoring and observability tools (Sentry, Prometheus, structured logging) and AI-specific metrics tracking.

Experience with automated testing frameworks and test-driven development practices.

Understanding of event-driven architecture and publish-subscribe patterns.

Experience with file processing, validation, and cloud storage integration for large-scale document ingestion pipelines.

Understanding of AI system performance optimization including batch processing, caching strategies, and model serving infrastructure.

Knowledge of modern development practices including type hints, linting (Ruff), and code quality tools.

Proficiency with AI-assisted development environments (Cursor IDE) and modern development workflows.

Requirements

Required Skills & Qualifications : 5+ years of professional Python development experience with mastery of async / await patterns and concurrent programming. Expert-level proficiency in FastAPI framework with experience building complex production APIs, middleware integration, and streaming responses. Advanced MongoDB expertise including aggregation pipelines, query optimization, schema design, replica sets, and performance tuning. Proven experience with RAG (Retrieval Augmented Generation) systems and implementing end-to-end document processing pipelines for intelligent search and Q&A applications. Hands-on experience with vector databases (Qdrant) for semantic search, embedding storage, and similarity matching at scale. Proficiency with LangChain framework including document loaders, text splitters, embedding models, vector stores, retrievers, and chain orchestration. Experience with real-time voice APIs and audio processing including OpenAI Realtime API. Hands-on experience with distributed task processing using Celery, Redis, and message queue systems (RabbitMQ / Redis). Proven experience integrating external APIs with sophisticated retry mechanisms, rate limiting, exponential backoff, and webhook implementations. Strong security implementation skills including JWT authentication, API security best practices, input validation, and secure file handling. Production experience with cloud platforms (Azure / AWS / GCP) including managed services, blob storage, and containerized deployments. Proficiency with Docker containerization, multi-stage builds, and container orchestration. Experience with database design, transaction management, connection pooling, and data migration strategies. Strong understanding of software architecture patterns, dependency injection, and separation of concerns