Sr Partner Agent Architect (UK)

parloasenior

In short

→Arquitecto técnico para integrar IA agente en empresas complejas.
→Trabajas con partners y clientes para diseñar soluciones de soporte con IA, desde arquitectura hasta conversaciones.
→Destaca por influir en la adopción a escala de IA agente en grandes empresas.

Proficiency in English is required.

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What they ask for

✓Experiencia en arquitectura de soluciones empresariales.
✓Conocimiento en integraciones con CRM, ERP y plataformas de contacto.
✓Capacidad para liderar sesiones técnicas con stakeholders.
✓Dominio de APIs REST, webhooks, JSON/XML.
✓Experiencia en diseño de flujos conversacionales con IA.
✓Capacidad de traducir requisitos de negocio en arquitectura técnica.

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REST APIswebhooksJSONXMLPostmanLLMsprompt engineeringembeddingscontext managementSSML

Who should you write to at parloa?

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About Parloa Parloa’s mission is to make every customer conversation feel effortless for both customers and the companies serving them. As agentic AI accelerates, Parloans are shaping the foundation of a new era in customer experience - one where customer support is no longer transactions, but meaningful exchanges. It is not just a vision; Parloa has powered over ONE BILLION interactions between global enterprise brands and their customers, with companies like Booking.com, HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale. About the role: As a Sr Partner Agent Architect at Parloa, you will operate at the intersection of enterprise solution architecture, conversational AI, and partner enablement, helping strategic partners and enterprise customers design, implement, and scale AI-driven customer experiences. This is a highly consultative, customer-facing role where you will guide partners and clients through solution discovery, end-to-end solution architecture, enterprise integration design, conversational architecture, and implementation strategy for enterprise AI Agents. You will design how Parloa’s platform integrates into complex enterprise environments, solve multi-system integration challenges, and apply systems thinking to build reliable, scalable AI solutions. While you bring strong technical depth and can build when needed, your primary focus will be helping partners shape the right technical solutions, architect scalable integrations, prioritize effectively, and successfully operationalize Parloa’s platform within complex enterprise environments. You will also help shape the conversational experience layer by translating customer requirements into AI Agent behavior through prompt engineering, LLM concepts, and conversational design. Prior conversational design experience is valuable but can be further developed on the job. You will work closely with strategic partners, enterprise customers, Partner Success Managers, Technical Program Managers, Forward Deployed Engineers, Solution Engineers, and the broader Agent Architect organization to drive successful AI deployments and long-term customer value. This is your opportunity to shape how enterprise organizations and global partners adopt agentic AI at scale while acting as a trusted advisor across both business and technical stakeholders. Areas of ownership: • Scope and design end-to-end AI Agent deployments across complex enterprise environments. • Define how Parloa integrates with systems such as CRMs, ERPs, ticketing platforms, contact center technologies, and other enterprise applications. • Apply systems thinking to solve complex multi-system data flows, dependencies, and integration challenges. • Guide partners and customers on API design, authentication, data transformation, field mapping, error handling, and integration patterns. • Build, configure, test, or troubleshoot integrations using REST APIs, webhooks, JSON/XML payloads, and tools such as Postman. • Collaborate with Forward Deployed Engineers on complex or custom integration scenarios beyond standard platform capabilities. • Lead technical discovery workshops, architecture reviews, and solution design sessions with partner and customer stakeholders. • Translate customer workflows and business requirements into structured conversational components and reliable AI Agent behavior. • Apply knowledge of LLMs, prompting strategies, embeddings, and context management to improve agent performance. • Support prompt design, conversational flows, guardrails, escalation logic, and voice configuration such as SSML, lexicons, and regex. • Apply structured testing to validate architecture, integration reliability, agent quality, and real-world behavior. • Review partn

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