Objective

We’re building an AI-first organization — and we’re looking for engineers who actually build, not just experiment. We’re hiring an AI Engineer to develop, integrate, and maintain AI-powered products across our ecosystem — from LLM-based customer experiences to internal copilots that transform how teams operate.

You’ll be part of a centralized AI Products Chapter, embedding into squads to bring real AI solutions into production.

What you’ll do

- Build and deploy Generative AI solutions (LLMs, RAG, agents, copilots) under standard production practices.

- Implement scalable AI components and services within production systems.

- Work across the full software lifecycle: assist in prototyping, deploy models, and optimize performance.

- Integrate AI models with real-world systems, APIs, data platforms, and backend workflows.

- Implement evaluation frameworks, monitoring mechanisms, and feedback loops to track model performance.

- Partner with Product, Data, and Engineering squads to deliver impactful AI-driven features.

What we’re looking for

- Solid software engineering background (Python + modern backend stack).

- Hands-on experience building with LLMs, Generative AI, or NLP frameworks.

- Practical experience deploying ML/AI features into production environments.

- Familiarity with cloud services (AWS/GCP), API design, and data pipelines.

- A strong problem-solving, execution-oriented, and continuous-learning mindset.

Why this role

- You won’t just build models → you’ll ship real AI products into production.

- You’ll collaborate across multiple squads → gain broad exposure and technical growth.

- You’ll contribute directly to shaping best practices for AI Engineering within the organization.

Required Knowledge & Experience





- Experience: 3–5 years of overall experience in Data & Tech, with at least 1.5–2 years of hands-on experience developing AI/ML and Generative AI solutions.

- Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related technical field.

- AI Competencies: Strong foundational understanding of Deep Learning, Natural Language Processing (NLP), and Generative AI (LLMs, RAG architecture, function calling, agents).

- Technical Stack: Proficiency in Python and familiarity with ML libraries (PyTorch or TensorFlow), alongside hands-on use of AI frameworks (LangChain, LlamaIndex, or Hugging Face).

- Cloud & Data Platforms: Hands-on experience with cloud-native AI/ML services (AWS SageMaker or Google Vertex AI) and standard data processing tools.

- Infrastructure & Tools: Practical experience using vector databases (Pinecone, Milvus, Qdrant, or Weaviate) and MLOps tools for model tracking and logging.

- Communication: Ability to clearly explain technical trade-offs and AI concepts to both technical teammates and product partners.

- Ethics & Compliance: Basic understanding of AI safety, data privacy, and responsible AI practices.

- Soft Skills: Proactive problem-solving, strong sense of ownership, willingness to learn, and commitment to writing clean, maintainable code.

If you’re excited about building real AI products (not just talking about them), we should talk. ? En Spin estamos comprometidos con construir un lugar de trabajo diverso e inclusivo.

Creemos en la igualdad de oportunidades y promovemos un ambiente libre de discriminación por motivos de raza, origen nacional, género, identidad de género, orientación sexual, discapacidad, edad o cualquier otra condición legalmente protegida.

📌 AI Engineer (México)
🏢 Spin - Job Board External
📍 México