The posting, in Parloa's own words
archived Sep 3, 2026About 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, Allianz, SAP, BarmeniaGothaer and TUI already deploying Parloa at scale.
About the Role:
As a Lead AI Agent Architect at Parloa, you will play a key role in transforming customer service through AI-powered agents. In this highly customer-facing role, you will lead the design and implementation of AI Agent solutions, helping enterprise customers and partners deliver more efficient, scalable, and intelligent customer experiences. You will work at the intersection of LLMs, conversational design, and enterprise systems , translating complex requirements into robust, production-ready AI workflows. From early solution design to deployment and optimization, you will ensure agents perform reliably, integrate seamlessly, and deliver measurable impact. This is your opportunity to design and deploy cutting-edge AI Agents at scale—shaping how enterprise companies leverage LLMs to transform customer experience and operational efficiency.
Read the full posting ↓
Areas of Ownership:
Lead the design and implementation of AI agent solutions, translating customer requirements into scalable conversational workflows and architectures Develop and refine LLM-driven agent behavior through prompt engineering, embeddings, and structured workflows Ensure high-quality, reliable performance through guardrails, testing, and continuous iteration based on data and feedback Break down complex processes into model-friendly interactions and optimize conversational flows (e.g., tone, SSML, logic) Design and deliver end-to-end solutions by integrating with enterprise systems (APIs, CRMs, backend services) Troubleshoot and resolve issues across workflows, integrations, and system behavior in production environments Collaborate cross-functionally with Engineering, Product, and Customer teams to ensure successful delivery and scalability Act as a trusted advisor to customers, guiding them on best practices and helping scale AI solutions across use cases Translate ambiguous business needs into structured solutions while challenging unrealistic requirements when needed Document best practices and contribute to building scalable knowledge and enablement assets across the team