Partner Value Solution Engineer
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Job Description
Partner Value Solution Engineer enabling partners to sell and deliver NICE’s AI-powered customer-experience software. Leading technical discovery, enablement, architecture, demos, and proof-of-value engagements.
Responsibilities:
- Serve as the technical bridge between NiCE and its partners, enabling them to position, sell, and deliver NiCE solutions
- Increase partner revenue and win rates through sales engineering, technical enablement, technical account management, and services support
- Own partner readiness across NiCE’s AI portfolio, including conversational AI, virtual agents, agent assist, automation, and AI-driven customer experience use cases
- Guide partners through discovery, use-case qualification, success criteria definition, demo flows, proof-of-value and pilot execution, and measurable outcome narratives
- Provide guidance on AI architecture, integrations, data requirements, model behavior, governance, and responsible AI
- Lead technical discovery engagements, map requirements to joint solutions and CCaaS/AI capabilities, and support tailored demos and POC engagements
- Build and deliver repeatable technical enablement programs, webinars, office hours, partner assets, and readiness plans
- Track partner feedback and communicate release impacts, integration gaps, model behavior, and roadmap needs
- Own technical relationships with key partners, manage integration patterns, assess release impacts, and support technical escalations
- Coordinate with Product and R&D on partner requirements and influence the NiCE product roadmap
- Support services scoping, estimates, SOW inputs, responsibility matrices, and architectural oversight for complex partner deployments
- Conduct advisory reviews, capture lessons learned, and incorporate them into patterns, templates, and enablement
Requirements:
- Experience with AI, conversational AI, virtual agents, agent assist, or automation in CX/contact center environments
- 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
- Experience supporting AI proof-of-values, pilots, or customer validation motions
Benefits:
- Fast-paced, collaborative, and creative work environment
- Opportunities to learn and grow
- Endless internal career opportunities across multiple roles, disciplines, domains, and locations
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