GenAI

About the Role

EdgeVerve is seeking a GenAI professional to advise clients on GenAI use cases, strategies, and provide feedback for product roadmaps. This role involves evaluating and recommending GenAI models, designing and prototyping GenAI features, and keeping up with advancements in AI technologies, including Gen AI and RAG. You will collaborate with engineering and design teams for product integration, and support pre-sales activities by providing GenAI expertise.

Key Responsibilities

• Advise clients on GenAI use cases and strategies.
• Provide feedback for product roadmaps.
• Evaluate and recommend suitable GenAI models and solutions for client problem statements.
• Design and prototype GenAI features and applications, focusing on user needs and value.
• Stay updated with the latest advancements in AI technologies, including Gen AI and RAG.
• Collaborate with engineering and design teams to ensure successful product integration.
• Collect, clean, and preprocess data using appropriate tools and libraries.
• Train, test, and evaluate AI models using appropriate evaluation metrics.
• Optimize and fine-tune models for performance, scalability, and efficiency.
• Implement and deploy AI solutions in production environments under different frameworks.
• Build applications and use appropriate prompting on generative AI models.
• Assess the ethical implications and risks associated with GenAI product deployments.
• Support pre-sales activities by providing GenAI expertise and contributing to product roadmaps.

Requirements & Tech Stack

• Ability to build applications and use appropriate prompting on generative AI models.
• Strong experience in Natural Language Processing, Large Language Models, and RAG approaches.
• Proficiency in programming languages such as Python, Java.
• Strong understanding of existing GenAI services.
• Strong understanding of data structures, algorithms, and AI project lifecycle.

Qualifications

• Bachelor's / Master's degree in Computer Science, Data Science, Engineering, or a related field.
• Strong hands-on background in AI, machine learning, deep learning, and statistical modeling.
• Strong analytical, problem-solving, and critical-thinking skills.
• Desire to investigate and try-out new tools and technologies as they are released.
• Ability to work under tight timelines, in cases for multiple project deliveries.
• Good interpersonal skills and ability to work effectively within high-performing teams.
• Confidence to convey technical advice and guidance to clients.
• Ability to adapt in a fast-paced multinational environment.
• Evidence of self-motivation for continuous development.