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

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

Benefits

Hardware — Laptop, smartphone, and ergonomic workstation fully provided
Books — Unlimited professional books via Kindle (device included)
Parental Leave — Extended maternity and paternity leave
Equity — Option pool participation available to all team members
PTO — 15 days of paid vacation per year from day one
Team Syncs — In-person team gatherings throughout the year
Villa Platzi — Annual full-company retreat somewhere in the world

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

PythonTypeScriptJavaScriptGoLLM integrationsRAG pipelinesrecommendation systemsdata pipelinesvector storesprompt engineering

Soft Skills

collaborationproduct instinctsproblem-solvingcommunicationadaptabilityuser-focused decision makingengineering rigormonitoring and evaluationiterationadvocacy for innovation