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About Ecomflow
Ecomflow is a global third-party logistics company serving e-commerce brands at scale. $60M+ in revenue, 100+ people, fully remote, bootstrapped. We handle fulfillment, shipping, and customer operations for brands selling across international markets.
We're building an AI function from the ground up. Not chatbots onto a landing page but building production systems that automate real operational work. Our CS AI agent already handles 12,500+ tickets per month. Our internal Slack agent answers SOPs, has multiple tools to navigate the functionalities in our dashboard. We're just getting started.
About the Role
You'll be the second AI hire, reporting directly to the AI Lead. You'll build, ship, and maintain AI-powered systems that automate operations across customer service, sales, marketing, and internal tooling.
You'll write production code that runs at scale, integrates with third-party systems, and saves the company real money. You'll own features end-to-end: from understanding the business problem, to designing the pipeline, to deploying and monitoring in production.
Key Responsibilities:
LLM pipelines - Design prompt chains, retrieval-augmented generation (RAG) systems, and structured output pipelines that connect business logic with AI models
API development - Build and maintain APIs and services that integrate AI capabilities into logistics operations (order management, tracking, customer communication)
Evaluation and monitoring - Run experiments, build eval datasets, and monitor AI system performance using Langfuse. Track accuracy, cost, and reliability metrics
Data processing - Develop background jobs for data ingestion, inference tasks, vector DB updates, and logistics workflows
Integrations - Connect AI systems with third-party tools: Zendesk, Slack, Notion, Mabang (order management), and others as needed
MCP servers - Build and maintain Model Context Protocol (MCP) servers that give AI agents structured access to internal systems, databases, and third-party APIs
AI-native WMS - Contribute to building Ecomflow's first AI-native warehouse management system, bringing intelligent automation to core logistics operations
Production systems - Deploy and maintain Cloudflare Workers, manage databases, and ensure AI systems are reliable and cost-efficient at scale
Tech Stack Languages: TypeScript, Python, SQL
Frameworks: Next.js, Cloudflare Workers
AI/ML: LLM APIs (Claude, OpenAI), vector databases, RAG pipelines, structured outputs
Infra: Cloudflare (Workers, D1, KV, R2), Langfuse (tracing, evals, experimentation)
Integrations: Zendesk, Slack, Notion, Mabang
Tools: Git, Linear, MCP (Model Context Protocol)
What We're Looking For Must-haves:- 2+ years of professional software engineering experience - Strong TypeScript and/or Python skills - you write clean, production-ready code - Experience building with LLM APIs (prompt engineering, structured outputs, tool use, RAG) - Comfortable with SQL databases and REST/GraphQL APIs - Can own a feature from problem definition through deployment and monitoring - Self-directed - you figure things out before asking, and you ship without being managed
Bonus points if: - Experience with Cloudflare Workers or serverless edge computing - Built eval pipelines or systematic prompt experimentation workflows - Experience integrating AI into existing business systems (not just greenfield projects) - Experience with MCP (Model Context Protocol) or building tool-use interfaces for AI agents - Familiarity with observability tools for AI (Langfuse, Braintrust, or similar) - Prior experience in logistics, e-commerce, or high-volume B2B operations
Who thrives here:- You're pragmatic. - You pick the simplest approach that solves the problem, not the most interesting one - You're autonomous. You don't wait for tickets to appear - you see problems and fix them - You're comfortable with ambiguity. AI work is iterative. You'll run experiments, throw things away, and try again - You communicate clearly. Remote team, async-first. Writing matters-
Details Location: Fully remote (company is Hong Kong-based, team is global) Reports to: AI Lead
Team: AI team, part of the engineering team at large
Type: Full-time
How to Apply : Send your CV and a short note about a production AI system you've built. Links to repos, demos, or write-ups are worth more than a cover letter.
