Role: Python Backend Developer – Gen AI
Experience: 4-8 Years
Work Location: Chennai / Bangalore
Job Description
skilled Python Backend Developer with hands-on experience in Generative AI (Gen AI) solutions. The ideal candidate will be responsible for building scalable backend systems, integrating AI/ML models, and contributing to the development of intelligent digital solutions. This role requires a strong foundation in Python, backend architecture, and familiarity with modern AI frameworks and APIs.
Key Responsibilities
Design, develop, and maintain scalable, high-performance backend services using Python and related frameworks (e.g., FastAPI , Flask , or Django ).
Integrate Gen AI models and APIs (such as OpenAI , Azure OpenAI , Anthropic , Hugging Face , etc.) into backend systems.
Develop APIs and microservices for AI-driven applications, ensuring robustness, security, and performance.
Collaborate with data scientists, ML engineers, and frontend developers to deploy AI/ML models into production environments.
Implement prompt engineering , model fine-tuning, and embedding-based retrieval (RAG) for intelligent application use cases.
Optimize backend architecture for scalability, reliability, and low latency.
Work with cloud platforms (AWS, Azure, or GCP) for model hosting, containerization, and deployment (Docker, Kubernetes).
Ensure proper testing , logging , and monitoring of backend services and APIs.
Stay updated with the latest advancements in AI, LLMs, and backend technologies to bring innovation into project solutions.
Required Skills and Experience
3-8 years of experience in backend development with a strong focus on Python .
Proficiency in one or more backend frameworks such as FastAPI , Flask , or Django .
Experience working with Generative AI tools, models, or APIs (e.g., OpenAI GPT, LangChain, Hugging Face Transformers).
Hands-on experience with RESTful APIs or GraphQL service design.
Strong understanding of data structures, algorithms, and system design .
Familiarity with LLM application development , prompt design , RAG pipelines , and vector databases (like Pinecone, Weaviate, FAISS, or Milvus).
Experience with CI/CD pipelines , Git , and containerization (Docker/Kubernetes).
Exposure to cloud deployment (AWS Lambda, Azure Functions, or GCP Cloud Run).
Excellent problem-solving, debugging, and communication skills.
Good to Have
Experience in microservices architecture and event-driven systems .
Knowledge of MLOps and model lifecycle management .
Exposure to data engineering tools (Kafka, Airflow, etc.).
Familiarity with frontend integration or full-stack development (React, Node.js, etc.).