AI Software Engineer

Platzi•San Francisco, CA

3d•$150,000 - $175,000

About The Position

Platzi is the largest technology school in the Hispanic world, with over 6 million students and 4,000 companies trusting us to deliver effective online education. Our mission is to make Latin America a technology superpower by training individuals and organizations in AI, Cybersecurity, English, Programming, and Leadership. As an industry leader, our presence is recognized through a massive and passionate community, extensive press coverage, and a daily stream of student success stories. We operate primarily remote, with key offices in Bogotá and Mexico City. We are looking for an AI Software Engineer to build the AI-powered features and systems that make Platzi's learning experience smarter, faster, and more personal. This is not a research role — it's an engineering role for someone who ships. You'll work across the full stack of AI integration: from designing the pipelines and APIs that power intelligent features, to making sure those systems are reliable, observable, and fast in production. You care about how things actually work for users, not just how they perform on a benchmark.

Requirements

3+ years of professional software engineering experience, with at least 1 year working on AI or ML-powered systems in production
Solid command of Python and at least one of TypeScript/JavaScript, Go, or a comparable backend language
Hands-on experience integrating LLM APIs and building AI-powered features — you've shipped things users actually use, not just internal demos
Familiarity with the modern AI engineering stack: LangChain, LlamaIndex, or equivalent frameworks; vector databases (Pinecone, Weaviate, pgvector); and prompt engineering best practices
Understanding of software fundamentals — system design, data structures, APIs, and how to build systems that fail gracefully
Experience with cloud infrastructure (AWS, GCP, or Azure), CI/CD pipelines, and production monitoring and observability tools
Strong product instincts — you know when AI is the right solution and when it isn't, and you make that call based on user impact, not hype

Nice To Haves

experience building recommendation or personalization systems
contributions to open-source AI projects
familiarity with edtech or consumer platforms at scale

Responsibilities

Design, build, and maintain production-grade AI features — including LLM integrations, RAG pipelines, recommendation systems, and intelligent automation across Platzi's platform
Own the full lifecycle of AI features from prototype to production: scoping, building, deploying, monitoring, and iterating based on real usage data
Integrate foundation models and third-party AI APIs (OpenAI, Anthropic, and others) into existing product surfaces with a focus on reliability, latency, and cost efficiency
Build and maintain the data pipelines, vector stores, and retrieval systems that power personalized and context-aware learning experiences
Write clean, well-tested, and well-documented code — you treat AI features with the same engineering rigor as any other production system
Collaborate closely with Product, Design, and the AI Lead to translate user needs into concrete technical solutions
Identify and implement guardrails, evaluation frameworks, and monitoring tools to ensure AI features behave predictably and safely at scale
Stay current with the evolving AI engineering landscape and advocate for adopting tools and patterns that genuinely move the product forward