6 Month Contract to Hire
Onsite 3 days/week – Hartford, CT
$55/hr-$65/hr
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, , 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
A high number of candidates may make applications for this position, so make sure to send your CV and application through as soon as possible.
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
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. xsgimln 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.