Conversational AI Engineer

EVERSANA•Overland Park, KS

4d•$100,000 - $125,000•Onsite

About The Position

The Conversational AI Engineer is responsible for designing, building, and supporting intelligent virtual agents using NICE Cognigy, with a focus on digital chat and conversational experiences. This role partners with business, IT, and experience design teams to create scalable, reliable chatbot and virtual assistant solutions that deflect contacts, streamline customer journeys, and integrate seamlessly with the broader contact center ecosystem. Experience with the Cognigy conversational AI platform is highly desirable to support advanced NLU, dialog orchestration, and enterprise‑grade automation use cases.

Requirements

Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related field, or equivalent practical experience.
3–5 years of experience developing or supporting conversational AI, chatbots, or virtual assistant solutions.
Hands‑on experience building chatbots using NICE Cognigy or comparable virtual agent platforms.
Strong understanding of conversational design, NLU concepts, intent modeling, and dialog management.
Experience integrating chatbots with enterprise systems using APIs and web services.
Experience supporting solutions in a production, enterprise IT environment.
Experience with chatbot development tools, NLU platforms, and analytics dashboards.
Familiarity with REST APIs, JSON payloads, and system integrations.
Experience using ticketing, backlog, and documentation tools (e.g., Jira, Confluence, ServiceNow).

Nice To Haves

Bachelor’s degree in a technical or analytical discipline.
Advanced coursework or training in systems analysis, product management, or customer experience technologies.
Hands‑on experience with the Cognigy conversational AI platform.
Experience supporting voice and digital virtual agents, including omnichannel handoff.
Experience tuning NLU models using real interaction data and transcripts.
Experience in large‑scale or regulated contact center environments.
Familiarity with AI‑assisted agent tools and downstream analytics.
NICE Cognigy certifications.
NiCE platform training or certification.
Agile, SAFe, or product delivery certifications.
Exposure to advanced NLU, LLM‑based conversational enhancements, or generative AI use cases.
Experience analyzing bot performance metrics and interaction outcomes.
Familiarity with security, privacy, and compliance considerations for customer interaction data.

Responsibilities

Design, build, test, and maintain NICE virtual agents, with a primary focus on digital chat and self‑service use cases.
Develop and manage conversation flows, intents, entities, dialog logic, and handoff scenarios to live agents across voice and digital channels.
Configure and tune natural language understanding (NLU) models to improve intent recognition, accuracy, and customer experience.
Implement and maintain integrations between Cognigy and backend systems, including CRM, knowledge bases, APIs, and automation services.
Support human handoff and omnichannel continuity, ensuring context is preserved when escalating from bot to live agent.
Monitor and optimize bot performance using analytics, transcripts, and interaction data to improve containment and task completion.
Troubleshoot and resolve production issues related to bot behavior, NLU accuracy, integrations, and platform performance.
Maintain detailed technical documentation for conversation designs, configurations, and integrations.
Ensure all conversational AI solutions comply with security, privacy, accessibility, and compliance standards.
Collaborate closely with Business Analysts, CX designers, product owners, and stakeholders during discovery and design workshops.
Participate in design reviews, backlog refinement, and release planning for virtual agent initiatives.
Communicate clearly with technical and non‑technical partners regarding bot capabilities, limitations, and release readiness.
Follow established change management, testing, and documentation standards for all chatbot deployments.
Stay current on advancements in conversational AI, NLU, generative AI, and chatbot design best practices.
Support production releases and provide after‑hours support as needed for critical issues.
Contribute to continuous improvement by identifying opportunities to expand self‑service and automation use cases.