IC4 - Sr AI Engineer

Spin - Job Board External; México; On-site; MXN 900,000 - 1,500,000; Full time

Job summary

Spin - Job Board External is seeking a Senior AI Engineer to design, develop, and scale AI-powered products across our ecosystem. You will join a centralized AI Products Chapter, embedding into squads to bring real AI solutions into production.

You’ll work across the full lifecycle from prototyping to deployment, integrating models with real systems, and building evaluation frameworks with monitoring and feedback loops to drive real impact.

Qualifications

• 7+ years in Data & Tech, with at least 3 years AI/ML in senior technical roles.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or related field.
• Deep understanding of Deep Learning, NLP, and Generative AI (LLMs, RAGs, Agents).
• Proficiency in Python (PyTorch, TensorFlow) and AI frameworks (LangChain, LlamaIndex, Hugging Face).
• Cloud-native AI services (AWS SageMaker or Vertex AI) and big data frameworks.
• Familiarity with vector databases (Pinecone, Milvus, Weaviate) and MLOps tools for model tracking.
• Ability to explain complex AI concepts to non-technical stakeholders in a business-centric way.
• Knowledge of AI governance, data privacy, and model interpretability.
• Proactive problem-solving, strategic thinking, and high-quality code.

Responsibilities

• Build and deploy Generative AI solutions (LLMs, RAG, agents, copilots).
• Design and implement scalable AI systems in production.
• Work across the full lifecycle: prototype → deploy → optimize.
• Integrate models with APIs, data platforms, workflows.
• Create evaluation frameworks, monitoring, and feedback loops.
• Partner with Product, Data, and Engineering to ship real impact.

Skills

Python

LLMs / Generative AI

NLP

Production ML systems

Cloud (AWS/GCP)

APIs & data pipelines

Problem solving

Stakeholder communication

Education

Bachelor’s or Master’s in Data Science, CS, or related field

Tools

PyTorch

TensorFlow

LangChain

LlamaIndex

Hugging Face

Pinecone / Milvus / Weaviate

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 a Senior AI Engineer to design, develop, and scale 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).
• Design and implement scalable AI systems in production.
• Work across the full lifecycle: prototype → deploy → optimize.
• Integrate models with real systems (APIs, data platforms, workflows).
• Create evaluation frameworks, monitoring, and feedback loops.
• Partner with Product, Data, and Engineering to ship real impact.

What we’re looking for

• Strong software engineering background (Python + modern stack).
• Hands‑on experience with LLMs / Generative AI / NLP.
• Experience building and deploying ML/AI systems in production.
• Familiarity with cloud (AWS/GCP), APIs, and data pipelines.
• Strong problem‑solving and execution mindset.

Why this role

• You won’t just build models → you’ll ship real AI products.
• You’ll work across multiple squads → high leverage impact.
• You’ll help define how AI Engineering is done at scale.

Required Knowledge & Experience

• Experience: 7+ years in Data & Tech, with at least 3 years specifically focused on AI/ML and hands‑on experience in senior technical roles.
  • Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or a related field.
• AI Expertise: Deep understanding of Deep Learning, Natural Language Processing (NLP), and Gen AI (LLMs, RAGs, Agents, etc.).
• Technical Stack: Proficiency in Python (PyTorch, TensorFlow) and experience with AI development frameworks (LangChain, LlamaIndex, Hugging Face).
• Cloud & Big Data: Experience in cloud-native AI services (AWS SageMaker or Google Vertex AI) and big data frameworks.
• Infrastructure: Familiarity with vector databases (Pinecone, Milvus, Weaviate) and MLOps tools for model tracking.
• Communication: Ability to explain complex AI concepts to non-technical stakeholders in a business-centric way.
• Ethics & Compliance: Knowledge of AI governance, including data privacy and model interpretability.
• Soft Skills: Proactive problem‑solving, strategic thinking, and commitment to high‑quality code and innovation.

If you’re excited about building real AI products (not just talking about them), we should talk.