Principal /Lead AI Engineer

Bridge Global; Ernakulam; Presencial; INR 1.200.000 - 2.400.000; Jornada completa

Descripción de la vacante

Bridge Global is seeking an AI/ML-focused role to design, develop, and deploy AI-powered applications leveraging LLMs, Gen AI, and ML technologies. You will build RAG systems, AI agents, chatbots, copilots, and automation solutions integrated with web apps, databases, and APIs.

The role involves evaluating models, fine-tuning for performance and cost, and shaping scalable AI architectures with vector databases and knowledge retrieval.

Responsabilidades

• Design, develop, and deploy AI-powered applications and solutions using Large Language Models (LLMs), Generative AI, and Machine Learning technologies.
• Build and maintain Retrieval-Augmented Generation (RAG) systems, AI agents, chatbots, copilots, and intelligent automation solutions.
• Integrate AI models and services with web applications, enterprise systems, databases, APIs, and third-party platforms.
• Evaluate, fine-tune, and optimize AI models for accuracy, performance, reliability, and cost efficiency.
• Develop prompt engineering strategies and testing frameworks to improve AI response quality and user experience.
• Design and implement scalable AI architectures, including vector databases, knowledge retrieval systems, and agent workflows.
• Collaborate with product managers, designers, QA engineers, and business stakeholders to translate requirements into AI-driven solutions.

Descripción del empleo

Roles & Responsibilities :

• Design, develop, and deploy AI-powered applications and solutions using Large Language Models (LLMs), Generative AI, and Machine Learning technologies.
• Build and maintain Retrieval-Augmented Generation (RAG) systems, AI agents, chatbots, copilots, and intelligent automation solutions.
• Integrate AI models and services with web applications, enterprise systems, databases, APIs, and third-party platforms.
• Evaluate, fine-tune, and optimize AI models for accuracy, performance, reliability, and cost efficiency.
• Develop prompt engineering strategies and testing frameworks to improve AI response quality and user experience.
• Design and implement scalable AI architectures, including vector databases, knowledge retrieval systems, and agent workflows.
• Collaborate with product managers, designers, QA engineers, and business stakeholders to translate requirements into AI-driven solutions.