WE ARE

The beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work. With over 45,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem.

POSITION 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 Gen AI models, algorithms, and methodologies to improve the overall quality Gen AI products, applications and systems.
• Analyze and evaluate the performance of Gen AI systems and provide design recommendations.
• Estimate the effort and time 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.
• Design LLM Ops solutions for large scale operationalization.
• 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 comprehensibly captures the intricate details of the language model, facilitating seamless understanding, efficient troubleshooting, and future development.
• Harness the power of transformer architecture, a cutting-edge deep learning model widely employed in natural language processing and computer vision, to optimize the language model’s performance and efficiency.
• Exploiting the transformative capabilities of transformer architectures to seamlessly process and reshape vast volumes of data, empowering the language model to achieve unprecedented levels of accuracy and versatility.