Proven experience in AI architecture and solution design with hands-on expertise in Kore.AI and other conversational AI platforms.
Deep understanding of NLP/NLU techniques and Generative AI models, including prompt engineering capabilities.
Strong programming skills in Python, Node.js, or JavaScript, plus experience with REST APIs, webhooks, microservices, and cloud platforms (Azure, AWS, GCP).
Experience leading enterprise AI initiatives with integration to enterprise systems, data pipelines, security/compliance, and cross-functional team leadership.
Requirements:
Architect scalable, enterprise-grade conversational AI solutions using Kore.AI and integrate bots with backend systems and third-party enterprise platforms.
Lead design, development, and deployment of intelligent bots with advanced NLP/NLU and Generative AI workflows.
Craft and optimize prompts for Generative AI, develop reusable templates, and translate business requirements into task-specific AI solutions.
Drive enterprise integration with applications (e.g., Salesforce, ServiceNow, SAP); ensure secure data exchange, monitoring, and alignment with business goals.
Job description
AI Architect US/Canada Engagement duration: 4-5 weeks Insurance background
Role AI Architect with expertise in Kore.AI, Natural Language Processing (NLP), Generative AI, Prompt Engineering, and Bot Development. As an AI Architect, the candidate will lead the design, development, and implementation of enterprise-scale conversational AI solutions. He/She will collaborate with business stakeholders, technical teams, and leadership to deliver intelligent, innovative, and scalable AI-powered applications that enhance user interactions and drive business outcomes. Key Responsibilities 1. AI Solution Architecture & Design
Architect scalable and enterprise-grade conversational AI solutions using Kore.AI and other industry-leading AI platforms.
Design end-to-end system architectures that integrate bots with backend systems, databases, and third-party enterprise platforms (e.g., CRM, ERP, ticketing tools).
Define and implement best practices for AI model deployment, orchestration, and monitoring.
2. AI & Bot Development
Oversee the design, development, and deployment of intelligent bots, ensuring they meet functional and performance requirements.
Implement advanced NLP/NLU techniques for accurate intent detection, sentiment analysis, and contextual understanding.
Utilize Generative AI models to develop sophisticated conversational workflows and natural language outputs.
3. Prompt Engineering
Craft and optimize prompts for Generative AI models (e.g., GPT) to ensure accurate, consistent, and business-aligned outputs.
Develop reusable prompt templates to accelerate AI solution delivery.
Collaborate with stakeholders to translate business requirements into task-specific AI solutions.
4. Enterprise Integration
Lead integration of conversational AI solutions with enterprise applications (e.g., Salesforce, ServiceNow, SAP).
Leverage APIs, SDKs, and microservices to enable seamless data exchange between bots and backend systems.