Senior Sales Engineer – Agentic AI for CX
New
C
CyaraCX technology
United StatesFull-TimeSenior
Salary$170,000 - $220,000 a year. This range indicates OTE.
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Job Details
- Experience
- 5+ years in pre-sales or solutions engineering
- Required Skills
- Prompt EngineeringCRM
Requirements
- Bring 5+ years of pre-sales or solutions engineering experience with C-level and VP-level stakeholders.
- Have a solid understanding of the CX technology stack, including CCaaS, IVR, CRM, and digital channels.
- Have proven experience with how AI agents and agentic workflows are built, deployed, and behave in CX environments.
- Know the agentic technology stack, including LLMs, RAG, tool calling, orchestration, and MCP.
- Have advanced prompt engineering skills, including reading agent system prompts and crafting adversarial test scenarios.
- Understand AI agent quality and compliance monitoring, including evaluation, hallucination detection, and policy adherence.
- Understand how testing, monitoring, and observability combine so production failures feed new tests.
- Be able to translate complex CX and AI requirements into technical solutions.
- Have a bachelor’s degree in Computer Science, IT, or a related field, or equivalent experience.
- Preferred: familiarity with customer AI agent platforms such as Cognigy, Sierra, Decagon, Observe.AI, AWS, and Google.
- Preferred: familiarity with CCaaS platforms such as NiCE, Genesys, Five9, Talkdesk, and AWS Connect.
- Preferred: experience with CX testing, monitoring, or observability tools, and familiarity with compliance and risk for AI in customer interactions.
Responsibilities
- Own technical sales engagements from first discovery through technical win.
- Lead discovery on customers’ CX technology stacks, AI agents, quality and compliance risks, and success criteria.
- Design closed-loop assurance solutions to test, monitor, and observe customers’ AI agents across their CX stacks.
- Deliver tailored demos, overviews, and workshops tied to customers’ AI agent quality and compliance goals.
- Scope and run proofs of concept that validate the platform against customer success criteria.
- Quantify the cost of AI failure and the efficiency gained through assurance for executive buyers.
- Partner with Sales, Product, and Implementation on RFPs, objections, and delivery handoffs.
- Create reusable demos and materials, and mentor teammates on agentic AI technology and prompt engineering.
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