Drive the end-to-end development and architectural migration of scalable chatbots and AI agents within the Microsoft ecosystem. Integrate enterprise systems using MuleSoft and optimize conversational flows through NLU and LLM orchestration.
Role Overview We are seeking a talented and passionateConversational AI Developer to play a pivotal role in managing current day chatbot implantations and designing, building, and optimizing our next-generation conversational experiences. In this role, you will bridge the gap between classical NLU systems and modern Generative AI orchestrations. You will be responsible for maintaining our robust enterprise foundations while actively driving our migration strategy toward autonomous agent frameworks.
The ideal candidate possesses a deep technical background in the Microsoft conversational ecosystem, a strong understanding of enterprise integration layers, and a passion for delivering seamless, human-like, yet transparent user experiences.
Key Responsibilities
End-to-End Development: Drive the full lifecycle development (from conversational design to production deployment) of scalable chatbots, virtual assistants, and AI agents.
Architecture Migration: Maintain and optimize our current Azure Bot Framework SDK v4 stack while actively participating in the architectural migration toward Microsoft Foundry and Agents 365 Azure SDK.
This is a Remote (work from home) position.
Enterprise Integration: Design and implement robust API integrations using MuleSoft as the central enterprise service bus to orchestrate data exchange between conversational front ends and core backend systems, including PeopleSoft and Salesforce.
Omnichannel Dialog Management: Author and manage rich, dynamic conversational interfaces using Microsoft Dynamics Adaptive Cards, Knowledge Management systems, and Automation Flows across web, mobile, and messaging channels.
Live Chat and Case Management: Build seamless escalation protocols, including live agent handoffs to Salesforce Live Chat and automated ticket routing via Salesforce Case Management APIs.
NLU and LLM Orchestration: Integrate Hybrid AI strategies by combining classical NLU (Azure Conversational Language Understanding/CLU) with Large Language Models (Azure OpenAI/GPT) for intelligent intent routing, fallback handling, and contextual content generation.
Performance Optimization: Analyze conversation logs, containment rates, and intent accuracy metrics using data visualization tools to continuously optimize conversational flows and minimize hallucinations.
Cross-Functional Collaboration: Partner closely with Product Managers, UX Designers, and business stakeholders to translate complex business logic into intuitive user stories and turn technical constraints into delightful user experiences.
Technical & Professional Qualifications Required Experience
3+ years of dedicated experience in software development with a specialized focus on Conversational AI, NLP/NLU, or LLM agent development.
Microsoft Bot Stack Expertise: Deep, hands-on proficiency with Azure Bot Framework SDK v4 (including Waterfall Dialogs, custom middleware, and state management) alongside experience or strong theoretical knowledge of Copilot Studio / Agents 365.
Core Backend Skills: Strong programming fundamentals with advanced proficiency in C#, .NET, and JavaScript, combined with frontend capabilities (HTML/CSS) for custom web-chat styling and Adaptive Card rendering.
Enterprise Systems Integration: Direct experience working with MuleSoft layers to pull/push data from legacy enterprise platforms like PeopleSoft and CRM systems like Salesforce.
Preferred Qualifications
Data and State Management: Experience configuring and querying Azure Cosmos DB for storing conversation state, user context, and telemetry logs.
Analytics Driven: Familiarity utilizing Power BI or Azure Application Insights to analyze drop-off points, intent confusion matrices, and chatbot containment metrics.
Modern DevOps: Experience defining and maintaining CI/CD pipelines for conversational assets across Dev, Test, and Production environments.
Industry Context: Experience implementing conversational solutions within Higher Education or complex, multi-stakeholder enterprise environments is a plus.
Soft Skills: Exceptional communication skills with the ability to articulate technical AI constraints to non-technical business stakeholders.
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