AI Engineering Lead: RAG, LLMs & Production ML

Blend; Santiago; Presencial; CLP 109.890.000 - 164.835.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

AWS Certifications

Databricks Certification

Snowflake Certification

AI learning paths

Udemy Business access

English lessons

Descripción de la vacante

Blend is seeking an AI Engineering Lead to drive end-to-end AI solutions, aligning data science with production-ready systems. You will mentor engineers, shape proposals, and define risk-aware AI architectures across RAG, prompting, and ML workflows.

The role emphasizes scalable inference, CI/CD for AI models, and collaboration with global teams. Advanced English and 6+ years of hands-on AI delivery are required. LATAM-friendly policies and remote options may apply.

Formación

• 6+ years of experience building and deploying AI solutions in production.
• Advanced English for global collaboration.
• Expert Python, strong Git and ML/LLM versioning practices.

Responsabilidades

• Lead end-to-end project delivery with governance and stakeholder communication.
• Mentor junior engineers and contribute to proposals and new business initiatives.
• Define AI system scope and communicate risks and tradeoffs clearly to clients.
• Design and build RAG systems, agentic frameworks, and LLM-powered solutions for production.
• Apply prompt engineering techniques including instruction design and few-shot sets.
• Lead feasibility assessments among prompting, RAG, fine-tuning, or classical ML.
• Design evaluation frameworks and go/no-go gates with custom metrics.
• Run structured experiments across prompts, retrievers, chunking strategies, and models.
• Identify model failure modes and remediation strategies.
• Build scalable inference infrastructure and CI/CD pipelines for AI/ML models.
• Automate the full MLOps/LLMOps lifecycle and design APIs/microservices.
• Optimize latency, cost, and reliability in orchestration layers.

Conocimientos

Python

Git

ML/LLM versioning

RAG experience

MLOps/LLMOps

APIs and microservices

Communication skills

IaC / infrastructure as code

Herramientas

MLflow

Weights & Biases

Databricks MLOps

AWS

Azure

GCP

Descripción del empleo

Blend is seeking an AI Engineering Lead to drive end-to-end AI solutions, aligning data science with production-ready systems. You will mentor engineers, shape proposals, and define risk-aware AI architectures across RAG, prompting, and ML workflows.

The role emphasizes scalable inference, CI/CD for AI models, and collaboration with global teams. Advanced English and 6+ years of hands-on AI delivery are required. LATAM-friendly policies and remote options may apply.