AI Software Engineer

Role Overview

AI Software Engineer responsible for building AI-powered features and systems that enhance Platzi's learning experience. This is a full-stack AI engineering role focused on shipping production-grade systems, not research.

Key Responsibilities

• Design, build, and maintain production-grade AI features including LLM integrations, RAG pipelines, recommendation systems, and intelligent automation
• Own the complete 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, etc.) into existing product surfaces with focus on reliability, latency, and cost efficiency
• Build and maintain data pipelines, vector stores, and retrieval systems powering personalized learning experiences
• Write clean, well-tested, and well-documented code with engineering rigor applied to AI systems
• Collaborate with Product, Design, and AI Lead to translate user needs into technical solutions
• Implement guardrails, evaluation frameworks, and monitoring tools ensuring AI features behave safely at scale
• Stay current with AI engineering landscape and advocate for adopting relevant tools and patterns

Requirements

• 3+ years professional software engineering experience with at least 1 year on AI/ML-powered systems in production
• Solid proficiency in Python and at least one of: TypeScript/JavaScript, Go, or comparable backend language
• Hands-on experience integrating LLM APIs and shipping AI-powered features to real users
• Familiarity with modern AI engineering stack: LangChain, LlamaIndex, or equivalent frameworks; vector databases (Pinecone, Weaviate, pgvector); prompt engineering best practices
• Understanding of software fundamentals: system design, data structures, APIs, graceful failure handling
• Experience with cloud infrastructure (AWS, GCP, or Azure), CI/CD pipelines, production monitoring and observability
• Strong product instincts to determine when AI is the right solution

Nice to Have

• Experience building recommendation or personalization systems
• Open-source AI project contributions
• Familiarity with edtech or consumer platforms at scale

Benefits

• Hardware: Laptop, smartphone, and ergonomic workstation provided
• Unlimited professional development books