AI Architect NTT DATA North America
NTT DATA North America
Office Location
Full Time
Experience: 5 - 5 years required
Pay:
Salary Information not included
Type: Full Time
Location: Karnataka
Skills: Technology Architecture, Machine Learning, AI Architect, Large Language Model LLM, natural language processing NLP, Neural Network, Generative Ai, Gen AI models, algorithm, Responsible AI Security
About NTT DATA North America
Job Description
AI Architect will play a pivotal role in designing and implementing the technology architecture for AI use cases (including Large Language Model (LLM)) platform systems and solutions. As an AI architect, you will translate business roadmap into technical requirements and architecture. This role will apply natural language processing (NLP) and machine learning concepts and experiences implementing real time business use cases. You will architect large language models (LLMs) and design neural network parameters, leveraging corpus of unlabeled structured and unstructured data, to further enhance the model's capabilities. Responsibilities: Architect and design end to end Generative AI products, applications and solutions for specific business needs and provide implementation guidance during delivery. Leverage, customize and implement available Gen AI models, algorithms, and methodologies to improve the overall quality Gen AI products, applications and systems. Analyze and evaluate the performance ofGen AIsystems and provide design recommendations. Hands on implementation and troubleshooting supports of Gen AI solutions. Estimate the effort, time and cost required for deploying an end-to-end solution using LLMs. Estimate cost of using LLMs in different forms for business use cases and the viability, develop cost models for different usage patterns. Analyze and make right technological choices for generative ai solutions. Design and prototype reusable components for LLM based solution patterns. Architect components of an LLM solution to address Responsible AI & Security. Collaborate seamlessly with diverse, cross-functional teams to accurately identify and prioritize requirements, ensuring that the language model meets the needs and expectations of various stakeholders. Create and maintain comprehensive technical documentation that captures the intricate details of the technical architecture, language model, efficient troubleshooting, and future development and maintenance.,