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about 1 month ago
Requirements and responsibilities
Role OverviewWe are seeking a technically deep, hands-on Solutions Engineer with strong enterprise contact center and customer experience expertise, combined with a startup and builder mindset, to lead the design, prototyping, and hardening of AI-driven solutions for large enterprise prospects.This is not a traditional demo-focused Sales Engineer role. This role operates as an applied AI systems architect and builder in a pre-sales environment. You will translate enterprise workflows into structured, demo-ready AI architectures and personally build working prototypes that validate feasibility under real-world constraints.You must be comfortable owning technical design end-to-end, operating with high autonomy, executing under executive visibility, and driving technical outcomes without relying heavily on downstream teams.What You’ll DoApplied AI Solution ArchitectureDesign and prototype enterprise-grade, AI-driven customer experience demo solutions, translating business logic into structured reasoning frameworks.Architect robust retrieval, orchestration, and validation systems, building scalable prototypes that tolerate real-world data variability.Own the transition from early-stage prototype to hardened proof of concept.Enterprise CX & Contact Center ExpertiseApply deep knowledge of enterprise contact center ecosystems, including CCaaS, CRM, ticketing systems, digital messaging, routing logic, escalation flows, QA models, and reporting structures.Work directly with CX, Operations, Digital, IT, and Architecture stakeholders to understand real-world workflows and constraints.Convert operational processes into AI-enabled workflows that align with containment, handle time, SLA, QA, escalation rate, and customer satisfaction metrics.Identify integration patterns across enterprise systems and design practical implementation approaches.Enterprise Discovery & Technical NavigationLead rigorous technical discovery sessions across multi-layered enterprise organizations.Extract clear architecture and data requirements from ambiguous or politically complex environments.Identify logic gaps, data fragmentation, compliance constraints, and integration risks early in the engagement.Document architecture, assumptions, and technical success criteria clearly.Strategic Pre-Sales PartnershipPartner closely with Account Executives to shape technical strategy within enterprise accounts.Scope engagements realistically, balancing ambition with execution feasibility.Articulate architectural tradeoffs clearly to both executive and technical audiences.Influence enterprise stakeholders on integration patterns and AI implementation approaches.Contribute to scalable solution design that supports long-term account expansion.Execution ExpectationsOperate independently in fast-moving, ambiguous environments.Rapidly build working prototypes under tight timelines.Take full ownership of technical outcomes rather than relying on downstream teams to validate feasibility.Design with production realities in mind, not just happy-path demonstrations.Maintain a consistently high conceptual and technical bar in AI-driven systems.Deliver artifacts that withstand executive and architectural scrutiny.Required ExperienceEnterprise CX & Contact Center Background5+ years of experience in enterprise customer experience, contact center, or customer support technology environments.Strong familiarity with CCaaS platforms, CRM systems, routing frameworks, digital messaging channels, escalation models, and reporting metrics.Experience modeling solutions against operational KPIs including containment, AHT, SLA, escalation rate, QA score, and CSAT.Demonstrated experience working with enterprise stakeholders across Operations, IT, Digital, and Architecture teams.Enterprise Stakeholder NavigationProven ability to lead technical discovery in complex, multi-stakeholder enterprise accounts.Experience extracting structured requirements from ambiguity.Track record of influencing architectural decisions and technical direction within enterprise environments.Comfortable pushing back constructively on scope, feasibility, and risk.Applied AI & Systems EngineeringHands-on experience building AI-driven applications using large language models or similar technologies.Experience structuring reasoning flows, orchestration logic, and decision frameworks.Practical experience designing retrieval strategies across structured and unstructured knowledge sources.Strong Python proficiency including API client development, data normalization, error handling, and test harness construction.Experience building lightweight internal tools or utilities to accelerate solution development.Experience debugging multi-system interactions across AI behavior, logic layers, and integration layers.Familiarity with version control and structured testing practices.Cloud & Integration FoundationsWorking knowledge of cloud architecture patterns, including event-driven systems, middleware, and scalable API design.Experience integrating enterprise SaaS platforms using REST APIs and webhooks.Understanding of data modeling, schema design, and system scalability considerations.Familiarity with at least one major cloud platform.Startup & Builder MindsetExperience operating in high-growth startups or similarly fast-paced environments.Demonstrated history of building complex systems independently.Comfortable operating without rigid structure or fully defined requirements.High ownership mentality with minimal dependency on external resources.Bias toward shipping validated, working systems over producing theoretical designs.What Sets You ApartYou move from whiteboard architecture to working prototype in days, not weeks.You design systems that withstand real-world enterprise constraints.You think in workflows, integration boundaries, and measurable outcomes.You are equally comfortable discussing routing logic with contact center leaders and debugging APIs or AI behavior.You hold a high technical standard and proactively design guardrails and validation into your builds.Success in This Role Looks LikeIndependently leading technical discovery that results in clearly documented architecture and defined success criteria.Delivering production-grade proofs of concept that withstand executive and architectural scrutiny.Identifying integration, data, and logic risks before late-stage deal pressure.Shipping working technical artifacts that reduce reliance on downstream teams.Translating AI system behavior into measurable operational and financial impact.This Role Will Not Be a Fit IfYou prefer highly structured requirements before beginning work.You are uncomfortable being the primary technical owner in high-visibility enterprise deals.You rely heavily on product or engineering teams to validate feasibility before building.You view pre-sales primarily as presentation-driven rather than execution-driven.Who This Role Is ForThis role is ideal for a technically strong builder with deep enterprise CX experience who wants to operate at the intersection of AI engineering and enterprise solution architecture.You are comfortable navigating executive conversations, designing scalable integration patterns, and personally building the systems that validate your architectural thinking.If you are seeking a traditional demo-focused Sales Engineer role or one centered primarily on slideware and handoffs, this role will not be the right fit.Benefits and Perks:Market-competitive total compensation package100% company paid family medical and 100% individual dental and vision insurance coverageFlexible, unlimited vacation policyStock optionsStrong company cultureQuiq is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure people feel supported and connected at work. Applicants need to have the authority to work in the US. As we are at an early stage, immigration sponsorship is not available.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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