Artificial Intelligence Developer (AI) (Mumbai)

Role & responsibilities - Design, develop, and deploy AI/ML and Generative AI solutions using Python and up-to-date AI frameworks. - Build and maintain LLM-based applications, including RAG pipelines, AI agents, and prompt-based systems. - Develop scalable backend services using FastAPI / Flask / Django for AI-powered applications. - Integrate and optimize Large Language Models (OpenAI, Azure OpenAI, AWS Bedrock, etc.) into production systems. - Design and implement vector database solutions for semantic search and retrieval (ChromaDB, Pinecone, FAISS). - Work on data pipelines, ETL processes, and preprocessing workflows for AI model training and inference. - Deploy AI applications on cloud platforms (AWS / Azure / GCP) ensuring scalability, reliability, and cost efficiency. - Collaborate with cross-functional teams (product, data science, engineering) to deliver end-to-end AI solutions. - Optimize model performance, latency, and accuracy in production environments. - Implement CI/CD pipelines and containerized deployments using Docker and DevOps practices. - Monitor, debug, and improve deployed AI systems for reliability and performance. Preferred candidate profile - Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field. - 26+ years of experience in AI/ML, Data Engineering, or Backend Development (depending on seniority level). - Strong proficiency in Python programming and object-oriented design principles. - Hands-on experience with LLMs, RAG systems, and Generative AI applications. - Experience with FastAPI / Flask / Django and building RESTful APIs. - Good understanding of vector databases, embeddings, and semantic search systems. - Familiarity with cloud platforms (AWS Bedrock preferred, Azure OpenAI or GCP acceptable). - Knowledge of SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB). - Exposure to CI/CD pipelines, Docker, and basic DevOps practices. - Experience with LangChain / LangGraph / prompt engineering is a strong plus. - Strong problem-solving ability and experience building production-grade AI systems. - Good communication skills and ability to work in a collaborative team environment. - Passion for learning and staying updated with evolving AI/GenAI technologies. Role & responsibilities - Design, develop, and deploy AI/ML and Generative AI solutions using Python and up-to-date AI frameworks. - Build and maintain LLM-based applications, including RAG pipelines, AI agents, and prompt-based systems. - Develop scalable backend services using FastAPI / Flask / Django for AI-powered applications. - Integrate and optimize Large Language Models (OpenAI, Azure OpenAI, AWS Bedrock, etc.) into production systems. - Design and implement vector database solutions for semantic search and retrieval (ChromaDB, Pinecone, FAISS). - Work on data pipelines, ETL processes, and preprocessing workflows for AI model training and inference. - Deploy AI applications on cloud platforms (AWS / Azure / GCP) ensuring scalability, reliability, and cost efficiency. - Collaborate with cross-functional teams (product, data science, engineering) to deliver end-to-end AI solutions. - Optimize model performance, latency, and accuracy in production environments. - Implement CI/CD pipelines and containerized deployments using Docker and DevOps practices. - Monitor, debug, and improve deployed AI systems for reliability and performance. Preferred candidate profile - Bachelors or Masters degree in Computer Science, AI/ML, Data Science, or related field. - 26+ years of experience in AI/ML, Data Engineering, or Backend Development (depending on seniority level). - Strong proficiency in Python programming and object-oriented design principles. - Hands-on experience with LLMs, RAG systems, and Generative AI applications. - Experience with FastAPI / Flask / Django and building RESTful APIs. - Good understanding of vector databases, embeddings, and semantic search systems. - Familiarity with cloud platforms (AWS Bedrock preferred, Azure OpenAI or GCP acceptable). - Knowledge of SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB). - Exposure to CI/CD pipelines, Docker, and basic DevOps practices. - Experience with LangChain / LangGraph / prompt engineering is a strong plus. - Strong problem-solving ability and experience building production-grade AI systems. - Good communication skills and ability to work in a collaborative team environment. - Passion for learning and staying updated with evolving AI/GenAI technologies.