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AI Engineer Manager

Blend · Montevideo

Remote
Remote Senior 🇬🇧 English
Prompt engineering Agentic frameworks MLOps LLMOps CI/CD pipelines Microservices Orchestration

Description du poste

About the role

Blend is looking for an AI Engineer Manager to join its LATAM team in a remote, full‑time capacity. You will lead the design, development, and production deployment of cutting‑edge AI systems that deliver tangible value for clients.

Key responsibilities

  • Lead end‑to‑end AI project delivery, ensuring governance, stakeholder communication, and reliable execution.
  • Design and build robust Retrieval‑Augmented Generation (RAG) pipelines, agentic frameworks, and LLM‑powered solutions for production.
  • Apply advanced prompt engineering techniques, including few‑shot prompting, structured outputs, and tool/agent prompts.
  • Conduct feasibility assessments to select the optimal technical approach (prompting, RAG, fine‑tuning, classical ML, or hybrid).
  • Develop evaluation frameworks using LLM‑as‑a‑judge, custom metrics, recall@k, precision@k, and go/no‑go gates.
  • Run structured experiments across prompts, retrievers, chunking, embeddings, reranking, and model variants.
  • Identify and categorize model failures such as hallucinations and retrieval misses.
  • Build scalable inference infrastructure and CI/CD pipelines for AI/ML models.
  • Automate the MLOps/LLMOps lifecycle: tracking, versioning, deployment, monitoring, retraining, and continuous improvement.
  • Design APIs, microservices, and orchestration layers optimized for latency, cost, reliability, and scalability.
  • Mentor junior engineers and contribute to proposals, solution design, and new business initiatives.

Required profile

  • 6+ years of experience building and deploying AI, ML, or data‑driven solutions.
  • Proven ability to lead technical delivery and communicate effectively with stakeholders.
  • Strong analytical mindset with a focus on pragmatic AI system design.

Required skills

  • Prompt engineering
  • Retrieval‑Augmented Generation (RAG) pipelines
  • Agentic frameworks
  • LLM‑powered solution development
  • Evaluation framework design
  • MLOps / LLMOps lifecycle automation
  • CI/CD pipeline implementation for AI models
  • API development, microservices, and orchestration

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Blend

Montevideo