IC4 - Sr AI Transformation Analyst

Spin - Job Board External; Mexico; Remote; MXN 900,000 - 1,700,000; 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 and embed into squads to bring real AI solutions into production.

You’ll work on Generative AI, NLP, and production systems, using Python and modern AI stacks. Expect collaboration with Product, Data, and Engineering to ship impactful AI features at scale.

Qualifications

• 7+ years in Data & Tech, with at least 3 years in AI/ML.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Applied Mathematics, or related field.
• Proficient in Python (PyTorch, TensorFlow) and AI development frameworks.

Responsibilities

• Build and deploy Generative AI solutions (LLMs, RAG, agents, copilots).
• Design scalable AI systems for production.
• Work from prototype to deploy to optimize performance.
• Integrate models with real systems via APIs and data pipelines.
• Create evaluation frameworks, monitoring, and feedback loops.
• Partner with Product, Data, and Engineering to ship real impact.

Skills

Python

Generative AI

NLP

LLMs

Cloud computing

APIs

Data pipelines

Production deployment

Problem solving

Education

Bachelor’s or Master’s in Data Science / CS / Applied Mathematics

Tools

PyTorch

TensorFlow

LangChain

LlamaIndex

Hugging Face

AWS SageMaker

Google Vertex AI

Pinecone

Milvus

Weaviate

MLflow

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 businesscentric 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.