AI Agent Engineer, Internal Operations

Sendbird is on a mission to build the AI workforce of tomorrow. Sendbird is the omnichannel AI agent platform enterprises choose to elevate the customer experience by initiating autonomous support & sales conversations, keeping humans in the loop for complex inquiries, and re-engaging customers with proactive business messages. We are the omnichannel AI agent platform enterprises choose to elevate customer experience. Trusted by 4,000+ of the world’s most popular apps—including industry leaders like Match Group, Rakuten, Yahoo, and Coupang—Sendbird powers over 7 billion messages every month.

We’re looking for an AI Agent Engineer to help transform how our company operates, not by adding more people, but by multiplying the capability & throughput of every person who’s here.

Your mandate is simple but audacious: build, deploy, and orchestrate AI agents that 100× our internal productivity. You’ll sit at the nerve center of the company, working directly with the CEO and Chief of Staff, to identify, design, and launch autonomous systems that replace repetitive, and potentially complex workflows, augment decision-making with holistic data, and amplify execution velocity across every team and individuals.

And you won’t be handed tasks, you’ll go hunting for them based on the priorities discussed and set with the CEO and the executive team.  

This role requires an onsite schedule 5 days/week in our San Mateo, CA office.  

Why This Role Matters

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.

What You Will Do

• 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.

Who You Are

• 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

Bonus Superpowers

• Experience with multi-agent orchestration or workflow engines.
• Background in data engineering or MLOps for LLM applications.
• A track record of “automation art” — professional or passion projects where your systems replaced hours of cognitive work with seconds of autonomous reasoning.