Job Overview : We are seeking a Senior Backend Engineer with strong expertise in Python (Django or Flask) and a clear understanding of the entire software development lifecycle. The ideal candidate will have hands-on experience integrating Generative AI (LLMs) into real-world applications and working with tools like OpenAI APIs, LangChain, and vector databases. This role requires someone who can design robust backend systems, architect scalable AI-powered applications, and bridge traditional development with modern AI capabilities. Key Responsibilities: Design, develop, and maintain robust backend systems using Python (Django / Flask). Lead end-to-end development and deployment of applications with Generative AI (LLMs). Integrate OpenAI APIs, build prompt workflows, and implement RAG (Retrieval Augmented Generation) pipelines. Work with LangChain, Vector Databases (e.g., Pinecone, FAISS, Weaviate) to enable AI-based search and chat capabilities. Own the backend architecture of AI-enabled products including authentication, API integration, data pipelines, and performance tuning. Ensure scalable and secure deployment of backend services using Docker, CI/CD pipelines, and cloud platforms (AWS / Azure / GCP). Collaborate with frontend developers, AI/ML engineers, and product teams to translate business requirements into technical solutions. Follow and advocate best practices in SDLC, code quality, testing, and documentation. Required Skills & Qualifications: 6+ years of hands-on backend development experience in Python. Proficiency in Django or Flask for building REST APIs and backend systems. Strong understanding of the Software Development Lifecycle (SDLC) including agile methodologies. Deep experience with Generative AI / LLMs (e.g., OpenAI, Mistral, Claude, etc.). Experience with OpenAI APIs, LangChain, and prompt engineering. Good understanding of RAG architecture, vector databases, and unstructured data handling. Experience integrating third-party APIs and external systems. Strong skills in PostgreSQL / MongoDB / Redis. Familiarity with cloud infrastructure (AWS, GCP, Azure) and DevOps practices (Docker, CI/CD). Excellent problem-solving and debugging skills. Ability to mentor junior developers and contribute to system design discussions. Preferred Skills (Nice to Have): Experience with microservices architecture. Knowledge of event-driven architecture (e.g., Kafka, RabbitMQ). Exposure to frontend technologies like React.js is a plus. Hands-on experience with multi-modal models (e.g., text-to-image, audio). Prior work on chatbots, custom copilots, or AI assistants.
