Conversational AI Engineer

Conversational AI Engineer (Individual Contributor)

Onsite 3 days/week Hartford, CT

Visa: Any

Must Have Qualifications

• Strong experience as a full stack developer delivering complex, enterprise scale applications
• Hands on experience designing and implementing conversational AI solutions using IBM WatsonX Orchestrate or similar platforms (Dialogflow CX, Amazon Lex, Kore.ai, LivePerson)
• Proficiency in NodeJS/TypeScript and Java with Spring, building RESTful web services
• Solid understanding of scalable architecture patterns, data lifecycle management, and cloud native development
• Experience developing and deploying microservices on OpenShift or comparable container platforms
• Strong Agile experience, including breaking down user stories into tasks and estimating work within a SAFe delivery model
• Strong collaboration and communication skills across co located, cross functional teams

Nice to Have Qualifications

• Experience with Angular, React, HTML, CSS, JSP, or Python
• Familiarity with Speech to Text tuning and SSML for text to speech refinement
• Exposure to analytics and data platforms such as Tableau, Alation, DataRobot, or Trifacta
• Experience with CI/CD pipelines using tools such as Jenkins, GitHub, or Octopus
• Strong business acumen and interest in emerging AI and conversational technologies

Day to Day Overview

In this role, you will design, build, test, and deploy conversational AI solutions that deliver accurate, scalable, and context aware chatbot and voice experiences. You will participate in feature and user story refinement sessions, translate requirements into technical implementations, and develop conversational flows that integrate with enterprise APIs, cloud functions, and backend systems. You will collaborate closely with product managers, UI/UX designers, backend engineers, and other developers to ensure seamless end to end delivery. On a daily basis, you will troubleshoot, debug, tune, and optimize conversational agents across multiple channels, apply clean coding standards, and continuously improve conversational accuracy using NLP and training data best practices.