Pre Sales Engineer

At NiCE, we don’t limit our challenges. We challenge our limits. Always. We’re ambitious. We’re game changers. And we play to win. We set the highest standards and execute beyond them. And if you’re like us, we can offer you the ultimate career opportunity that will light a fire within you.

**So, what’s the role all about?
**As part of the Presales team, the AI Presales Engineer will work closely with Sales on discovery calls, technical deep dives, demos, and POCs, acting as a trusted advisor who bridges technology and business value

The Agentic Solution Sales Team combines an overlay and a hunter sales capacity to support advanced, AI solution sales cycles to accompany our CXone platform or be standalone.

The ideal candidate will have a deep understanding of advanced digital and AI technologies such as conversational AI, IVA, knowledge management, agent assistance and more. 

How will you make an impact?  

• Value Selling & Discovery: Partner with account executives to lead technical discovery sessions, identify high-value enterprise AI use cases, and articulate the ROI of automated agents.
• Rapid PoC Building: Design and build functional prototypes and workflow blueprints using n8n and LangChain to visually demonstrate value during the sales cycle.
• Solution Architecture: Translate client requirements into production-ready blueprints featuring RAG (Retrieval-Augmented Generation), semantic search, and secure enterprise app integrations.
• Technical Advisory: Serve as the trusted AI expert for client CTOs, IT directors, and business leaders, confidently handling security, data privacy, and architecture questions.
• Cross-Functional Feedback: Feed field insights and client requirements back into the Product and Engineering teams to influence the core product roadmap.

Have you got what it takes?

• Experience: 4–7 years of experience in a Pre-Sales Engineering, Solutions Architecture, or Technical Consulting role, with a strong focus on automation or generative AI solutions.
• Technical Comprehension: Deep conceptual and practical understanding of the AI ecosystem: workflow orchestration (n8n), LLM application frameworks (LangChain/LangGraph), and RAG pipelines.
• Value-Driven Mindset: Proven track record of value selling—translating technical features (like chunking, vector databases, or agents) into business outcomes (cost reduction, speed, risk mitigation).