Partner Value Solution Engineer

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.

Key Responsibilities

Sales Engineering: You will lead technical discovery engagements with partners, mapping customer requirements to joint solutions and NiCE's CCaaS/AI capabilities. You'll 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.

Increase partner revenue and win rates by making partners effective at selling and delivering NiCE solutions
Qualify AI use cases based on business value, technical feasibility, data readiness, and measurable outcomes.
Support AI-focused demos and PoVs that show business impact, not just capability.
Lead technical discovery sessions with partners
Map partner and customer requirements to joint solutions and CCaaS/AI capabilities
Support tailored demos that showcase integrated partner–vendor value rather than standalone features
Support proof-of-concept (POC) engagements with partners
Act as the technical trusted advisor to partner teams
Help acquire / validate architectures for customer solutions
Assist in crafting ROI stories that demonstrate joint solution value

Technical Enablement: You will build and deliver repeatable technical enablement programs to ramp partner SEs and solution architects. This includes maintaining partner-facing assets such as reference architectures, integration guides, and battlecards in the partner portal. You'll run ongoing readiness programs, webinars, office hours, and 30–60–90 day plans, to keep partners current on product updates, roadmap direction, and best practices.

Make partners as self-sufficient and effective as the NiCE SE team
Build AI-specific enablement around conversational design, prompt/design patterns, use-case discovery, PoV execution, responsible AI, and outcome measurement.
Track partner feedback on AI capabilities, implementation friction, model behavior, integration gaps, and roadmap needs.
Help partners understand release impacts tied to AI features, model updates, data dependencies, and governance.
Includes building reusable demo scripts, talk tracks, objection handling, and competitive positioning.
Ensure partner enablement stays aligned with the account team's strategy
Build repeatable technical enablement programs for partner SEs and architects
Deliver enablement to ramp new partner technical staff
Support competitive differentiators for partner teams
Keep partners current on product updates and new features
Keep partners aligned with the NiCE product roadmap
Share best practices across the partner ecosystem

Technical Account Management: You will own the end-to-end technical relationship with key partners, managing integration patterns, release impact assessments, and escalation paths. You'll coordinate with Product and R&D to surface partner-driven requirements and influence the product roadmap. You'll also govern architecture, security, and performance standards across partner solutions to ensure they meet joint quality benchmarks.

Ensure NiCE technology reliably delivers business value for customers
Manage integration patterns across partner solutions
Assess and communicate release impact to partners
Assist in escalation paths for technical issues
Coordinate with Product and R&D teams on partner-driven requirements
Manage and track technical feedback from partners
Influence the NiCE product roadmap based on partner input

Services: You will support scoping of services for partner-led implementations, including estimates, SOW inputs, and responsibilities matrices. You'll 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.

Support validation of services for partner-led implementations
Provide architectural oversight on complex partner deployments
Conduct advisory reviews on challenging implementation scenarios
Capture lessons learned from completed partner engagements
Feed lessons learned back into patterns and templates