[Remote] Product Pre-Sales Engineer, AI

Note: The job is a remote job and is open to candidates in USA. NiCE is an AI, cloud, and digital software company focused on customer experiences, financial crime prevention, and public safety. The Product Pre-Sales Engineer, AI designs, builds, and demonstrates AI-driven customer engagement solutions, leads technical discovery, develops proofs of value, responds to RFIs and RFPs, and provides expertise on Agentic AI solutions.

Responsibilities

• Lead discovery and solutioning. Own discovery calls and technical deep dives to uncover pain points and identify opportunities across NiCE's Agentic AI portfolio — including AI-driven Intelligent Virtual Agents, Knowledge Management, Agent-Assist, and Proactive AI
• Tell compelling stories. Deliver customized, high-impact demos and presentations that don't just show product features, they paint a vision of what exceptional customer experience looks like
• Respond to RFIs and RFPs. Craft differentiated responses that go beyond checkbox compliance and make NiCE stand out
• Design, build, and execute proof-of-value implementations that demonstrate real-world value and accelerate deal velocity
• Stay sharp on the competitive landscape. Continuously track market trends, competitive positioning, and emerging technologies across AI, digital, and cloud platforms
• Upskill others. Provide deep technical expertise and upskill others across adjacent teams, becoming a go-to subject matter expert for Agentic solutions in the NiCE portfolio
• Employees will also perform other reasonable related business duties as assigned by immediate supervisor and other management as required

Skills

• 7+ years in a solutions engineering, pre-sales, or sales architecture role, engaged in planning and executing complex enterprise software sales
• 7+ years of consulting or customer engagement experience
• 5+ years of contact center experience, with deep familiarity of the CCaaS landscape
• Proven track record delivering best-in-class solutions with strong work examples
• Hands-on ability to configure and demo AI agent flows including intent design, LLM tuning, RAG-based knowledge retrieval, and agent orchestration in Cognigy or a comparable conversational AI platform
• Working knowledge of voice technologies: SIP, WebRTC, IVR and voice gateway design, sufficient to architect and troubleshoot voice-channel POVs
• Ability to design and diagram integration architectures spanning CRM, knowledge bases, and business systems via REST APIs and microservices
• Familiarity with enterprise authentication protocols (OAuth, SAML, OIDC) and security/compliance frameworks relevant to AI deployments (e.g., PCI DSS, data governance, vendor security questionnaires)
• Understanding of agent observability and evaluation; able to speak to and demonstrate feedback loops, accuracy/reliability metrics, and guardrail testing in customer-facing conversations
• Working knowledge of HTML, JavaScript, CSS, DOM, and browser developer tools, plus basic scripting ability (Python/JavaScript) to support AI-assisted prototyping ("vibe coding") beyond no-code tooling
• Familiarity with MCP, A2A and multi-agent orchestration concepts, including multi-vendor agent interoperability (e.g., Salesforce, SAP, ServiceNow)
• Strong business acumen able to quickly understand new business processes and connect technology to revenue and profit outcomes
• Analytically minded with excellent problem-solving, presentation, and storytelling skills
• Ability to draw out root causes, not just symptoms, and apply creative thinking to solve them
• Skilled at managing multiple priorities and deliverables across concurrent client engagements

Company Overview

Company H1B Sponsorship