Conversational AI developer

• NTT DATA's Client is seeking a Conversational AI Developer to develop and implement conversational AI solutions: Design, build, and deploy chatbots and virtual assistants for banking use cases.
• Leverage LLMs and RAG: Utilize and fine-tune large language models (LLMs) and implement Retrieval-Augmented Generation (RAG) to enhance the accuracy and relevance of AI responses by incorporating domain-specific knowledge and real-time data.
• Design and execute Prompt Engineering strategies: Craft and optimize prompts for LLMs to elicit desired responses and ensure effective communication with users.
• Build and maintain robust data pipelines: Develop and manage data pipelines for training and deploying AI models, potentially using Graph Databases (Neo4j) to represent complex relationships within financial data (e.g., fraud rings, customer behavior).
• Implement NLP and NLU models: Develop and integrate NLP and NLU components for intent recognition, entity extraction, and sentiment analysis to understand user queries effectively.
• Ensure security and compliance: Implement strict security protocols and develop Guardrails to prevent misuse of AI systems and ensure compliance with banking regulations.
• Full-Stack Development: Contribute to both front-end and back-end development of conversational AI interfaces, ensuring a seamless user experience.
• Collaborate with cross-functional teams: Work closely with product managers, designers, and other engineers to deliver successful conversational AI solutions.
• Stay updated on latest trends: Keep abreast of the latest advancements in AI, machine learning, and conversational AI, particularly within the financial industry.

• Overall 10+ years of experience.
• Proficiency in programming languages: Python, JavaScript, R.
• Experience with NLP frameworks: spaCy, NLTK, BERT, GPT-based models.
• Strong experience in using Neo4J, Mongo DB
• Experience in developing and deploying conversational AI solutions, preferably in the banking or financial services sector.
• Strong proficiency in Python programming and related libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Experience with Large Language Models (LLMs), Prompt Engineering, and RAG implementation.
• Hands-on experience with Graph Databases like Neo4j, including understanding graph data modeling and querying.
• Experience with relational databases (Oracle) and NoSQL databases (MongoDB).
• Understanding NLP and NLU concepts and techniques.
• Knowledge of security best practices, including the implementation of Guardrails.
• Experience in full-stack development, including front-end (e.g., React, Angular) and back-end (e.g., Fast API, .NET Core) technologies.
• Excellent problem-solving and analytical skills.
• Strong communication and collaboration skills.

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