We are seeking a highly skilled and innovative AI-Powered Automation Engineer to design, implement, and optimize an advanced AI-driven chatbot automation solution that enhances the IT support experience for healthcare professionals. This chatbot automation will act as a first line of defense, providing automated, intelligent solutions for common IT issues, while ensuring secure handling of sensitive healthcare data.
As an integral member of our team, you will harness the power of Natural Language Processing (NLP), Machine Learning (ML), and intelligent automation to revolutionize IT support. Your role will involve integrating the chatbot automation with internal knowledge bases, ticketing systems, and leveraging cutting-edge NLP and ML techniques to automate IT issue resolution and optimize user interactions.
Key Responsibilities:
Design, build, and maintain an AI-driven chatbot automation that handles a variety of healthcare IT support tasks such as incident triage, password resets, system troubleshooting, and ticket creation.Ensure high availability, reliability, and scalability of the chatbot to meet the growing demands of healthcare IT support.Intent Recognition: Implement and optimize intent classification models to identify user queries (e.g., system issues, password reset requests) using algorithms like BERT, GPT, and fine-tuned transformers.Entity Extraction: Develop advanced models for extracting essential information (e.g., system names, error codes, timestamps) to improve resolution accuracy.Contextual Understanding: Implement systems that track conversation context across multiple turns, maintaining continuity in dynamic user interactions.Dialogue Management: Design decision-making frameworks and use machine learning models for seamless interaction management. This includes building decision trees and optimizing multi-turn conversations to simulate human-like behavior.Automated Issue Resolution: Integrate the chatbot with internal knowledge repositories, enabling the bot to provide self-service solutions for routine IT issues (e.g., FAQs, troubleshooting guides, software installation manuals).Continuous Update: Develop mechanisms for the knowledge base to be dynamically updated and improve over time through user feedback and AI-driven recommendations.IT Ticket Automation: Design and implement seamless integration with internal IT ticketing systems (e.g., ServiceNow, Jira Service Management, or similar platforms) to auto-generate, update, and track support tickets in real-time.Automated Prioritization and Escalation: Leverage machine learning models to predict the urgency of issues and trigger appropriate actions, such as prioritizing critical tickets or escalating unresolved issues.Model Development: Design, train, and fine-tune ML models for tasks such as intent classification, issue categorization, priority prediction, and automatic ticket routing using deep learning techniques (e.g., BERT, RNNs, LSTMs, and reinforcement learning).Continuous Model Improvement: Implement techniques for continuous learning, allowing models to adapt to evolving healthcare IT support challenges and new issues.Bot Performance Analytics: Monitor chatbot performance using key metrics (e.g., resolution time, user satisfaction, issue escalation rates) and feedback loops to fine-tune algorithms and improve response accuracy.User-Centric Optimization: Regularly update the chatbot’s capabilities based on user feedback, healthcare IT trends, and evolving technology to maintain a user-friendly, high-performance chatbot solution.