Are you ready to build the future of Latin America? 🚀
At Rappi, we build the SuperApp that changes the lives of millions of people every day. We are a team driven by speed, execution, and real results.
This is where things happen. If you are excited by solving real-scale problems, learning at record speed, and seeing the impact of your ideas in a matter of days, this is your place.
Want to build AI agents that millions of users use every day? 🤖
The challenge
At Rappi, we are building our AI Assistant: conversational agents that solve real needs for users, partners, and Rappitenderos in 9 LatAm countries. We are looking for an AI Engineer II with an end-to-end builder profile: someone who understands the business and the product, designs and takes LLM-based agents to production, and measures their success by the value they generate, not by the complexity of the model.
Your challenges
Design, build, and take conversational agents for the AI Assistant to production end-to-end
Translate business and product problems into agent use cases with measurable impact
Design the context strategy: prompts, tools, memory, and knowledge sources
Build and integrate MCP servers and skills that connect agents to Rappi's systems
Define evals, monitor quality, cost, and latency, and iterate based on data
Work with Product, Design, Data, and business teams to prioritize and launch features
Document agent-building patterns and best practices for the team
You will be a great fit
Experience: 2-4 years in software engineering, with at least 1 year building products on LLMs
Demonstrable experience taking agents or conversational assistants to production with an impact on a real business
Education: Completed university degree in Engineering, Computer Science, or a related field
English: Intermediate-advanced
Portfolio, repositories, or demos of agents built (preferred)
Previous experience at tech startups, in e-commerce, or marketplaces (preferred)
Tech profile
What you need to master
Building conversational agents with LLMs (OpenAI, Anthropic, Gemini) in production
Context Engineering: system prompts, memory, RAG, and context-window management
Model Context Protocol (MCP): building and integrating servers and tools
Agent Skills, tool use, and function calling to orchestrate multi-step workflows
Agent frameworks (LangGraph, OpenAI Agents SDK, Claude Agent SDK, or similar)
Agent evaluation and observability (evals, LLM-as-judge, guardrails, cost and latency monitoring)
Python and/or TypeScript (NodeJS)
Integration with APIs, microservices, and databases (SQL, NoSQL, vector stores)
Cloud (AWS), Docker, and CI/CD
Git
What makes you different
End-to-end builder mindset and ownership
Product thinking and business understanding
Results orientation and measurable impact
Clear communication with technical and business stakeholders
Collaboration and teamwork
Learning agility in a rapidly changing AI ecosystem
Bias to action: experiment, iterate, and launch quickly with good judgment
Attention to detail in quality and user experience
We believe our talent deserves the best tools to make an impact with purpose.
Mexico 🇲🇽
At Rappi, diversity makes us stronger
We believe diverse and inclusive teams build the best products, and we actively seek people of all genders, ages, backgrounds, religions, and sexual orientations. If you want to build the future of Latin America, your place is here.
Will you join the team? At Rappi, the limit is the one you set for yourself. If you are excited about learning in motion and building solutions that scale to millions, we want to meet you.