Sr Agent Architect
Pubblicato il 19-10-2026 - Senovo Capital Management in Milano
About ParloaParloa’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 , HealthEquity, Allianz, SAP, BarmeniaGothaer, and TUI already deploying Parloa at scale.
L'esperienza richiesta ai candidati, così come le competenze e le qualifiche aggiuntive necessarie per questo lavoro, sono elencate di seguito.
About the roleAs a Sr Agent Architect at Parloa, you will act as a solution architect for enterprise AI Agent deployments. You will design end-to-end system architectures that connect Parloa's platform to complex enterprise environments, solve multi-system integration challenges, and apply systems thinking to build reliable, scalable AI solutions for global enterprise clients.
You will also shape the conversational experience layer, using prompt engineering and your knowledge of LLMs to translate customer requirements into agent behavior. Architecture and integration depth are the core of this role. Conversational design skills are valued and can be developed on the job.
Areas of ownership
- Design end-to-end solution architectures for AI Agent deployments, mapping how Parloa's platform integrates into customers' enterprise systems (CRMs, ERPs, ticketing systems, contact center platforms).
- Build and configure integrations using integration platforms and APIs, applying systems thinking to solve complex, multi-system data flows.
- Collaborate with Forward Deployed Engineers on complex or custom integration scenarios that go beyond standard integration capabilities.
- Apply structured testing approaches to validate architecture, integration reliability, and AI agent performance und