IC3 - AI Engineer

Spin - Job Board External; México; On-site; MXN 900,000 - 1,400,000; Full time

Job summary

Spin - Job Board External is hiring an AI Engineer to develop, integrate, and maintain AI-powered products across the ecosystem. You will embed in squads within a centralized AI Products Chapter, delivering production-ready AI features and copilots.

Ideal candidates have 3–5 years in Data & Tech, hands-on AI/ML with Python, and experience deploying AI in production using LangChain, RAG, and cloud services. This role offers growth and exposure to end-to-end AI systems.

Qualifications

• 3–5 years of Data & Tech experience with hands-on AI/ML development.
• Bachelor’s or Master’s in Data Science, CS, Applied Math, or related field.
• Strong fundamentals in Deep Learning, NLP, and Generative AI (LLMs, RAG, function calling, agents).
• Proficiency in Python and ML libraries (PyTorch or TensorFlow) and AI frameworks (LangChain, LlamaIndex, Hugging Face).
• Experience with cloud-native AI/ML services (AWS SageMaker or Vertex AI) and data processing tools.
• Experience with vector databases (Pinecone, Milvus, Qdrant, Weaviate) and MLOps for tracking/logging.
• Clear communication of trade-offs and AI concepts to teams and partners.
• Basic understanding of AI safety, data privacy, and responsible AI practices.

Responsibilities

• Build and deploy Generative AI solutions (LLMs, RAG, agents, copilots) in production.
• Implement scalable AI components and services within production systems.
• Work across the full software lifecycle: prototype, deploy models, optimize performance.
• Integrate AI models with real-world systems, APIs, data platforms, and backend workflows.
• Implement evaluation frameworks, monitoring, and feedback loops to track model performance.
• Collaborate with Product, Data, and Engineering squads to deliver AI-driven features.

Skills

Python

LLMs

Generative AI

NLP frameworks

AWS/GCP

Education

Bachelor's or Master's in Data Science or CS

Tools

LangChain

LlamaIndex

Hugging Face

PyTorch

TensorFlow

Job description

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.