Enterprise AI Agent Architect for Partner Enablement

Parloa; London (KY); On-site; USD 140,000 - 180,000; Full time

Job summary

Parloa is seeking a Sr Partner Agent Architect to operate at the intersection of enterprise solution architecture, conversational AI, and partner enablement. You will guide partners and clients through discovery, end-to-end solution design, and enterprise integration to scale AI-driven customer experiences.

You will design integrations for complex environments, address multi-system data flows, and shape the conversational layer through prompt engineering and LLM concepts.

Qualifications

• 4+ years in enterprise customer-facing technical roles (solution/ systems architecture, integration, or complex SaaS).
• Experience with strategic partners, SI firms, or partner-led delivery models.
• Strong systems thinking across multiple systems and data sources.
• Experience with enterprise SaaS platforms (CRMs, ERPs, ticketing, contact centers).
• Proficiency in REST APIs, JSON/XML, Postman, OAuth, API keys, JWT.

Responsibilities

• Scope and design end-to-end AI Agent deployments across complex enterprise environments.
• Define how Parloa integrates with CRMs, ERPs, ticketing platforms, and other enterprise apps.
• Apply systems thinking to multi-system data flows and integration challenges.
• Lead architecture sessions, workshops, and design reviews with partners and customers.
• Translate requirements into reliable prompts, conversational flows, and agent behaviors.

Skills

REST APIs

JSON/XML

Postman

OAuth

JWT

English proficiency

Tools

MuleSoft

Boomi

Workato

SAP Integration Suite

Job description

Parloa is seeking a Sr Partner Agent Architect to operate at the intersection of enterprise solution architecture, conversational AI, and partner enablement. You will guide partners and clients through discovery, end-to-end solution design, and enterprise integration to scale AI-driven customer experiences.

You will design integrations for complex environments, address multi-system data flows, and shape the conversational layer through prompt engineering and LLM concepts.