AI Engineer

Job Description

Zycus is looking for passionate and curious AI Engineers - Intern who are excited to build intelligent solutions while working closely with customers and product teams. This hybrid internship combines AI Engineering with Product Support, providing hands-on experience in developing AI-powered applications, troubleshooting enterprise SaaS products, and driving customer-centric product improvements.

As an AI Engineer – Product Support Intern, you will contribute to the development of AI/LLM-based features while also supporting customers by analyzing issues, identifying root causes, and collaborating with engineering teams to deliver effective solutions. This role is ideal for candidates who enjoy both coding and solving real-world business problems.

Key Responsibilities

• Design, develop, test, deploy, and maintain AI/ML and Generative AI solutions using Large Language Models (LLMs), Natural Language Processing (NLP), and modern AI frameworks to build intelligent, scalable enterprise applications.
• Perform data preprocessing, analysis, feature engineering, model training, optimization, and performance tuning to improve the accuracy, scalability, reliability, and efficiency of AI-driven solutions.
• Integrate AI models and services with enterprise applications through APIs and other integration technologies to deliver seamless business workflows.
• Research, evaluate, and implement emerging AI technologies, tools, frameworks, and industry best practices to drive innovation and continuously enhance product capabilities.
• Provide technical support for AI-powered enterprise applications by troubleshooting functional and technical issues, performing root cause analysis, managing incidents, and collaborating with engineering teams to ensure timely issue resolution.
• Serve as the primary technical point of contact for customer queries through email, chat, and calls, ensuring prompt communication, effective problem resolution, and high levels of customer satisfaction.
• Support product configuration, feature validation, User Acceptance Testing (UAT), release testing, production monitoring, and quality assurance activities to ensure reliable product performance and successful deployments.
• Monitor AI feature performance and application health, analyze customer feedback and product usage trends, and recommend enhancements that improve user experience, product quality, and business value.
• Drive automation initiatives, optimize support processes, and contribute to operational excellence by creating and maintaining technical documentation, knowledge base articles, standard operating procedures, project reports, and solution documentation.
• Collaborate closely with Product Management, Engineering, Quality Assurance (QA), Customer Success, Technical Account Management (TAM), and other cross-functional teams to deliver customer-centric AI solutions, translate customer requirements into actionable product improvements, and support continuous product innovation.