AI Engineer Manager
Blend · Montevideo
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