Senior Agent Architect

Role overview

Join a team building agentic AI for enterprise customer conversations, where the goal is replacing transactional support interactions with intelligent, reliable exchanges. As a Senior Agent Architect, you act as a solution architect for enterprise deployments of AI agent technology, owning end-to-end architecture and integration across complex customer environments.

Responsibilities

- Design end-to-end solution architectures for AI agent deployments, mapping how a conversational platform plugs into CRMs, ERPs, ticketing systems, and contact center platforms - Build and configure integrations using APIs and integration platforms, applying systems thinking to multi-system data flows - Collaborate with deployment engineers on integration scenarios that exceed standard platform capabilities - Validate architecture, integration reliability, and agent performance through structured testing under real-world conditions - Scope deployments, providing strategic architecture advice and execution support to customers and partners - Use knowledge of LLM internals to translate customer requirements into reliable prompts and conversational flows - Fine-tune conversational output, including voice tuning patterns, to align with customer brand standards - Document best practices and product capabilities for internal and external audiences

Requirements

- 3+ years in customer-facing enterprise roles with proven solution architecture, systems architecture, or enterprise integration experience - Strong systems thinking applied across multiple systems and data sources - Experience with complex SaaS implementations at scale, including CRMs, ERPs, contact center platforms, and ticketing systems - Proficiency with REST API design, JSON/XML data structures, API testing tools, and authentication patterns such as OAuth, API keys, and JWT - Analytical mindset with risk-assessment and stakeholder-management skills

Nice to have

- Conversational design, prompt engineering (chain-of-thought, few-shot learning), or A/B testing experience - Familiarity with embeddings and other LLM internals - Conversational fluency with attention to subtle nuances in agent behavior

Benefits and work setup

- On-target earnings of $156,000–$178,000 USD, plus equity - Multi-stage recruiting process including technical interviews and a bar-raiser round - Work tied to GDPR, ISO, and ISO 27001-aligned data protection standards