AI Agent Engineer, Sendbird

• You’re an engineer who builds and iterates fast, and thinks systemically — capable of connecting APIs, data streams, and workflows into cohesive autonomous systems
• Fluent in modern AI stacks (Python, TypeScript, LLM APIs, LangChain, vector databases, retrieval pipelines)
• Deep empathy for how organizations and businesses actually operate — you can sit in a finance meeting or customer success review and instantly spot what should or could be automated
• Obsessed with velocity, leverage, and compounding productivity. You believe an AI agent should not just do human work faster — it should do what humans never had time to imagine
• You’re as comfortable in the command line as you are in the boardroom
• You're strongly aligned to our 7 core values

Desirable

• This is not an R&D lab project — this is the AI nerve center of the company
• You’ll work shoulder-to-shoulder with the CEO and Chief of Staff to redefine how a high-velocity organization operates in an AI-default world
• The agents you design, build, and deploy will literally become part of our workforce — compounding productivity across every function
• Architect, build, and deploy internal AI agents that can reason over unstructured data (Slack, google docs, google sheets, email, cloud & AI infrastructures, data warehouse, dashboards, CRMs, ERP, finance, accounting, etc.) and act autonomously — e.g., automating tasks, scheduling follow-ups, generating insights, or coordinating actions across systems
• Identify and map inefficiencies across functions (e.g., Revenue Ops, People Ops, Finance & Accounting, Marketing, Sales, Customer Success, and even Product Development) and build agentic automations that compress time and cognitive load, and boost productivity, if not automate completely
• Prototype and ship fast — from prompt graphs to fine-tuned models, toolchains, and LLM orchestration frameworks (LangChain, OpenDevin, etc.)
• Collaborate across boundaries: work with every department to re-imagine workflows through AI-first mindset and leverage, not incremental efficiency
• Instrument productivity metrics — measure and visualize the before/after impact of agent deployment on velocity, decision quality, and throughput
• Teach and evangelize the adoption of AI and agents across the organization to enable as many employees as possible to become 100x employees
• Stay at the frontier of emerging LLMs, retrieval frameworks, and agentic architectures, bringing the latest techniques directly into production