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 1,600 professionals dedicated to generative AI, leveraging the depth and experience of more than 40,000 AI and data professionals across the company our Generative AI and LLM Center of Excellence 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.
• Develop large language model (LLM)-based applications using open source frameworks like A2A, MCP, Semantic Kernel, LangChain, Llama Index.
• Adapt LLMs to improve performance, accuracy and alignment of the general-purpose models
• Develop and integrate LLMs and/or LLM applications into products and services.
• Implement AI applications that comply with ethical guidelines and legal standards, particularly regarding data privacy and user consent based on the technical design.
• Analyze and evaluate the performance of Gen AI systems and provide design recommendations.
• 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.