AI Forward Deployed Engineer

NiCE is a global company known for its innovative AI and digital solutions. The AI Forward Deployed Engineer will be responsible for designing and deploying AI-driven customer engagement solutions, collaborating with customers to translate complex challenges into intelligent automation.

Responsibilities:

• Design and build AI-driven virtual agents that automate customer service workflows across digital and voice channels
• Develop intelligent automation using the NiCE AI and Digital portfolio, including conversational AI, knowledge systems, and omnichannel engagement capabilities
• Architect agent behaviors including intent handling, workflow orchestration, and multi-system interactions
• Continuously refine and evolve agents through iterative testing, model tuning, and performance optimization
• Own the full lifecycle of AI agents from initial design through deployment and ongoing optimization
• Define agent architecture including prompting strategies, knowledge retrieval patterns, and decision logic
• Implement observability, evaluation, and feedback loops to improve agent accuracy, reliability, and business outcomes
• Monitor agent performance and evolve agents to handle increasingly complex customer interactions
• Build integrations between AI agents and enterprise systems including CRM, commerce platforms, knowledge bases, and operational systems
• Develop APIs, services, and orchestration layers enabling agents to perform real business transactions
• Implement multi-step workflows that coordinate API calls across multiple systems of record
• Ensure secure, scalable, and reliable integrations across customer environments
• Build full-stack solutions that support agent interactions including web interfaces, backend services, and integration layers
• Develop prototypes and working applications that demonstrate end-to-end AI automation scenarios
• Create reusable components and frameworks that accelerate development of new AI agent capabilities
• Maintain and enhance demo environments and development environments used for solution innovation
• Partner directly with customers to understand operational challenges and identify opportunities for AI-driven automation
• Translate business requirements into technical architectures and working solutions
• Build prototypes, proof-of-value implementations, and production-ready agent capabilities
• Act as a trusted technical advisor to both business and technology stakeholders
• Collaborate with product, engineering, and sales teams to identify product gaps and innovation opportunities
• Prototype new capabilities that extend the NiCE AI platform
• Provide direct field insights that inform product roadmap and future platform capabilities
• Contribute reusable patterns, integrations, and architectures that improve future deployments
• Design and build advanced technical demonstrations showcasing AI-driven customer experiences
• Develop reusable demo frameworks and environments that illustrate enterprise use cases
• Support sales engineering and presales teams in communicating the value of AI-driven customer engagement solutions
• Enable internal teams with technical knowledge of AI agents, integrations, and platform capabilities

Requirements:

• Deep technical expertise across full-stack development, AI agent architectures, APIs, integrations, and conversational automation
• Ability to collaborate directly with customers and business leaders
• Design and build AI-driven virtual agents that automate customer service workflows across digital and voice channels
• Develop intelligent automation using the NiCE AI and Digital portfolio, including conversational AI, knowledge systems, and omnichannel engagement capabilities
• Architect agent behaviors including intent handling, workflow orchestration, and multi-system interactions
• Continuously refine and evolve agents through iterative testing, model tuning, and performance optimization
• Own the full lifecycle of AI agents from initial design through deployment and ongoing optimization
• Define agent architecture including prompting strategies, knowledge retrieval patterns, and decision logic
• Implement observability, evaluation, and feedback loops to improve agent accuracy, reliability, and business outcomes
• Monitor agent performance and evolve agents to handle increasingly complex customer interactions
• Build integrations between AI agents and enterprise systems including CRM, commerce platforms, knowledge bases, and operational systems
• Develop APIs, services, and orchestration layers enabling agents to perform real business transactions
• Implement multi-step workflows that coordinate API calls across multiple systems of record
• Ensure secure, scalable, and reliable integrations across customer environments
• Build full-stack solutions that support agent interactions including web interfaces, backend services, and integration layers
• Develop prototypes and working applications that demonstrate end-to-end AI automation scenarios
• Create reusable components and frameworks that accelerate development of new AI agent capabilities
• Maintain and enhance demo environments and development environments used for solution innovation
• Partner directly with customers to understand operational challenges and identify opportunities for AI-driven automation
• Translate business requirements into technical architectures and working solutions
• Build prototypes, proof-of-value implementations, and production-ready agent capabilities
• Act as a trusted technical advisor to both business and technology stakeholders
• Collaborate with product, engineering, and sales teams to identify product gaps and innovation opportunities
• Prototype new capabilities that extend the NiCE AI platform
• Provide direct field insights that inform product roadmap and future platform capabilities
• Contribute reusable patterns, integrations, and architectures that improve future deployments
• Design and build advanced technical demonstrations showcasing AI-driven customer experiences
• Develop reusable demo frameworks and environments that illustrate enterprise use cases
• Support sales engineering and presales teams in communicating the value of AI-driven customer engagement solutions
• Enable internal teams with technical knowledge of AI agents, integrations, and platform capabilities
• Experience with Large Language Models
• Knowledge of prompt engineering
• Familiarity with agent orchestration frameworks
• Understanding of retrieval-augmented knowledge systems
• Experience with conversational AI architecture
• Proficiency in backend services and APIs
• Experience with web and conversational interfaces
• Knowledge of integration layers
• Experience with data pipelines
• Familiarity with REST APIs and microservices
• Experience with CRM and business system integrations
• Knowledge of knowledge systems and data stores
• Understanding of identity and access management