Technical Customer Success Manager - Conversational AI Or Agentic AI

We need to output HTML fragment with sections only if real specific content. Use

for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must not repeat job title as heading. No Job ID etc. Remove boilerplate. Must preserve all substantive info. No invented details. No placeholder sections. We need to parse the posting: It includes description of role, impact, responsibilities, requirements, qualifications, personal attributes, advantage if you also have, about Cognigy NiCE, about NiCE, requisition ID, reporting into, role type, etc. We need to extract sections. We must not include sections like Benefits, Pay, Schedule unless posting actually states them. The posting does not mention benefits, pay, schedule. So we should not include those headings. We need sections: About the role (maybe a short description), Responsibilities (the "How will you make an impact?" bullet list), Requirements/Qualifications/Skills (maybe combine). The instruction says use headings for those categories if content exists. We can have multiple sections: About the role, Responsibilities, Requirements, Qualifications, Skills. But we should avoid thin sections. Perhaps combine Requirements and Qualifications into one? But they said use headings for each if content exists. We can decide to have sections: About the role, Responsibilities, Requirements (including experience, technical expertise, personal attributes, advantage). Skills could be part of Requirements. But we need to follow instruction: "Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It suggests we can use those headings if we have content. It's okay to have multiple. We must not create sections with filler like "commensurate with experience". We have concrete content. Let's extract: About the role: The introductory paragraph: "At NiCE, we don’t limit our challenges... So, what’s the role all about? We are looking for a Technical Customer Success Specialist to support our Customer Success Managers (CSMs) by providing deep technical expertise across a portfolio of enterprise customers. This role is designed to scale technical knowledge across the Customer Success organization and act as a technical backbone for day-to-day account engagement. You will work in a one-to-many model, partnering with multiple CSMs and supporting approximately 30–50 customer accounts. Your focus will be on answering technical questions, advising on best practices, and helping customers successfully design, operate, and optimize conversational AI solutions built on the Cognigy platform. This role sits at the intersection of Customer Success, Product, and Conversational AI expertise." That's substantive. Responsibilities: The "How will you make an impact?" bullet list items: - Act as a shared technical resource for CSMs across multiple enterprise accounts - Support CSMs with technical topics related to platform usage, solution design, product functionality, demos and best practice - Provide timely responses to technical questions from CSMs and, where appropriate, directly from customers - Serve as an escalation point for complex “how does this work” or “how should we do this” questions - Conversational AI & Platform Expertise - Advise customers on conversational AI best practices, including dialog design, intent modeling, and flow orchestration - Support NLU configuration, training, testing, and optimization - Provide guidance on the application of generative AI and agentic AI concepts within enterprise conversational solutions - Help customers understand platform capabilities, limitations, and recommended patterns - Contact Center & Enterprise Context - Support customers operating conversational AI solutions within contact center environments (voice and digital) - Provide high-level guidance on integrations with CCaaS, CRM, and backend systems - Help customers troubleshoot issues related to conversation behavior, routing, and experience design - Collaboration & Feedback Loop - Collaborate closely with Support, Product, Engineering, and Professional Services to resolve customer issues - Identify recurring themes, gaps, or improvement opportunities and feed insights back to internal teams - Contribute to internal documentation, enablement materials, and best-practice guides for CSMs - Scale & Efficiency - Help standardize technical guidance across the customer base - Enable CSMs to handle more technical conversations independently over time - Improve internal processes and documentation to support a growing enterprise customer footprint We can format as

• each. Requirements: The "Have you got what it takes?" section includes: - 3–5 years of experience in conversational AI, virtual agents, or intelligent automation - Experience in a customer-facing technical role (Customer Success, Solution Consulting, Technical Support, or Professional Services) - Experience supporting enterprise customers in a one-to-many or scaled model - Technical Expertise - Strong understanding of conversational AI fundamentals, including: - NLU concepts (intents, entities, training data, evaluation) - Generative AI and LLM-based conversational systems - Agentic AI and multi-step orchestration patterns - Solid understanding of contact center operations and customer service workflows - Ability to analyze conversational behavior and explain technical concepts to non-technical stakeholders - Personal Attributes - Structured, organized, and comfortable juggling multiple customers and priorities - Clear communicator with a pragmatic, solution-oriented mindset - Curious and eager to stay current with advancements in conversational and generative AI - Strong sense of ownership and customer focus Qualifications: Could be same as Requirements? Might separate "You will have an advantage if you also have:" as Qualifications or Skills. But we can treat that as "Preferred Qualifications". However instruction says we can have Qualifications section if real specific content. The advantage list is: - Hands-on experience with enterprise conversational AI platforms - Familiarity with Cognigy or similar products - Experience working with voice automation and CCaaS integrations We could put that under Qualifications. Skills: Could be derived from technical expertise and personal attributes. But we might avoid duplication. Perhaps we combine Requirements and Qualifications and Skills into one section? But they ask to use headings if content exists. We could have sections: About the role, Responsibilities, Requirements, Qualifications. Skills maybe not needed separately. But we need to preserve all substantive info. If we put technical expertise and personal attributes under Requirements, that's fine. Advantage list under Qualifications. We must not include sections like Benefits, Pay, Schedule. Now produce HTML fragment:

  About the role

  ...

  Responsibilities

  • ...
  ...

  Requirements

  • 3–5 years of experience in conversational AI, virtual agents, or intelligent automation
  • Experience in a customer-facing technical role (Customer Success, Solution Consulting, Technical Support, or Professional Services)
  • Experience supporting enterprise customers in a one-to-many or scaled model
  • Technical Expertise
    • Strong understanding of conversational AI fundamentals, including:
    • NLU concepts (intents, entities, training data, evaluation)
    • Generative AI and LLM-based conversational systems
    • Agentic AI and multi-step orchestration patterns
    • Solid understanding of contact center operations and customer service workflows
    • Ability to analyze conversational behavior and explain technical concepts to non-technical stakeholders
  • Personal Attributes
    • Structured, organized, and comfortable juggling multiple customers and priorities
    • Clear communicator with a pragmatic, solution-oriented mindset
    • Curious and eager to stay current with advancements in conversational and generative AI
    • Strong sense of ownership and customer focus
  But nesting
  inside
  • is okay but might be messy. Could instead use

    for subheadings but not allowed? Only

    for section headings. We can use

    for prose and

    • for lists. For subpoints we can just include them as
    • with dash or colon. Simpler: flatten. We can list each bullet as
    • with the content. Thus Requirements list items: - 3–5 years of experience in conversational AI, virtual agents, or intelligent automation - Experience in a customer-facing technical role (Customer Success, Solution Consulting, Technical Support, or Professional Services) - Experience supporting enterprise customers in a one-to-many or scaled model - Strong understanding of conversational AI fundamentals, including: NLU concepts (intents, entities, training data, evaluation); Generative AI and LLM-based conversational systems; Agentic AI and multi-step orchestration patterns - Solid understanding of contact center operations and customer service workflows - Ability to analyze conversational behavior and explain technical concepts to non-technical stakeholders - Structured, organized, and comfortable juggling multiple customers and priorities - Clear communicator with a pragmatic, solution-oriented mindset - Curious and eager to stay current with advancements in conversational and generative AI - Strong sense of ownership and customer focus That covers. Qualifications (advantage): - Hands-on experience with enterprise conversational AI platforms - Familiarity with Cognigy or similar products - Experience working with voice automation and CCaaS integrations Now produce HTML. Check no boilerplate: we removed about Cognigy NiCE, about NiCE, requisition ID, reporting into, role type, equal opportunity etc. Those are boilerplate? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "About Cognigy NiCE" and "About NiCE" might be considered boilerplate? It's company description, not strictly legal/EEO. Might be considered substantive? The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. The company description could be considered substantive? However it's not about the role. The sections we have are About the role, Responsibilities, Requirements, Qualifications. The company description might be considered extra but not required. The instruction says remove duplicated lines, but not necessarily remove company overview. However they said "Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate". The "About Cognigy NiCE" and "About NiCE" are not those. Could be considered substantive but maybe not needed for the role. The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." If we omit the company description, we are summarizing away detail (removing it). So we should keep it? But where to put? Could be part of About the role? Might be separate section "About the company". But we only have allowed headings list; we could add a section like "About the company" but not in list. The instruction says use

      for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It gives examples but not exclusive. Could we add another heading like "About the company"? Might be okay but they'd expect only those headings? Safer to include company info within About the role paragraph. We can incorporate a brief sentence about NiCE and Cognigy within About the role. But we must not invent. We can copy the sentences: "About Cognigy NiCE ... About NiCE ..." We can include them as a paragraph after the role description. Thus About the role paragraph will include the role description plus the company description. Let's craft:

      We are looking for a Technical Customer Success Specialist to support our Customer Success Managers (CSMs) by providing deep technical expertise across a portfolio of enterprise customers. This role is designed to scale technical knowledge across the Customer Success organization and act as a technical backbone for day-to-day account engagement. You will work in a one-to-many model, partnering