Partner Value Solution Engineer

About the role

The NiCE Partner Value Solution Engineer is part of the excellence team dedicated to empowering NiCE's partner ecosystem to confidently position, sell, and deliver NiCE solutions. This multifaceted role spans sales engineering, technical enablement, technical account management, and services, all united by a single goal: increasing revenue and win rates by making partners effective at selling and delivering NiCE solutions.

Responsibilities

• Sales Engineering: Lead technical discovery engagements with partners, map customer requirements to joint solutions and NiCE's CCaaS/AI capabilities. Support tailored demos and proof-of-concept (POC) engagements that highlight integrated partner–vendor value, and serve as the technical trusted advisor helping partners shape architectures, proposals, and ROI narratives that win deals.
• Technical Enablement: Build and deliver repeatable technical enablement programs to ramp partner SEs and solution architects. Maintain partner-facing assets such as reference architectures, integration guides, and battlecards in the partner portal. Run readiness programs, webinars, office hours, and 30–60–90 day plans to keep partners current on product updates, roadmap direction, and best practices.
• Technical Account Management: Own the end-to-end technical relationship with key partners, manage integration patterns, release impact assessments, and escalation paths. Coordinate with Product and R&D to surface partner-driven requirements and influence the product roadmap. Govern architecture, security, and performance standards across partner solutions to ensure they meet joint quality benchmarks.
• Services: Support scoping of services for partner-led implementations, including estimates, SOW inputs, and responsibilities matrices. Provide architectural oversight on complex deployments to ensure technical deliverability of what was sold, and capture lessons learned to feed back into patterns, templates, and future partner enablement.

Qualifications

• Experience with AI, conversational AI, virtual agents, agent assist, or automation in CX/contact center environments
• The ability to translate business outcomes into AI use cases and success criteria
• Working knowledge of LLMs, generative AI, AI orchestration, integrations, and responsible AI principles; and experience supporting AI PoVs, pilots, or customer validation motions.