Senior Agent Architect

About the role

As a Senior Agent Architect at Parloa, you will play a key role in transforming customer service with AI Agents. In this customer-facing role, you will support the implementation of Parloa's solutions, enhancing customer experiences for clients and partners. Using your expertise in Large Language Models (LLMs), Prompt Engineering, NLP & NLU conversational design, and integration platforms, you will craft effective AI workflows and build connections to enterprise systems and ensure quality, performance, and end-to-end operational readiness. You will design, prototype, and validate conversational solutions for AI agent deployments, including the integration layer that connects Parloa's platform to customers' existing technology stacks, and guide customers and partners in maximising the value of Parloa's AI solutions. This is your opportunity to architect and deliver cutting-edge AI agent solutions while influencing how enterprise customer service evolves in the age of generative AI. Areas of Ownership: Scope and implement AI Agent deployments, providing strategic advice and execution support to customers and partners. Leverage your knowledge of LLM internals (e.g., embeddings) to analyze customer requirements and design precise prompts for reliable, user-aligned behavior. Simplify complex workflows and processes into digestible conversational components, enabling LLMs to handle challenging tasks effectively. Fine-tune conversational flows and voice output (e.g., SSML, Lexicons, Regex) to align with customer brand standards. Build and configure integrations between customers' systems and Parloa's Platform, connecting external tools (e.g., CRMs, ERPs, ticketing systems, contact center platforms) via intergration platforms and APIs to deliver end-to-end enterprise solutions. Collaborate with Forward Deployed Engineers on complex or custom integration scenarios that go beyond standard integration capabilities. Identify and solve blockers together with other departments at Parloa (e.g. Product, Agent Integration Engineering, or Sales) and the customer. Apply structured testing approaches to validate AI agent behaviour, quality, and performance under real-world conditions. Document best practices, how-to guides, and product capabilities for internal and external audiences, representing the expertise of the Agent Architect team.