TrabajoAR
Presencial

Ai engineering manager

Empresa

Salario

A convenir

Jornada

Full-time

Modalidad

Presencial

Fuente

ar.linkedin.com

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Descripción

Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com

We are seeking an AI Engineering Manager to contribute to our next level of growth and expansion.

Job Description

Leadership and Delivery

Lead project delivery end to end, with clear governance, stakeholder communication, and accountability for outcomes

Build and mentor a high-performing AI engineering team, establishing technical standards and fostering a culture of quality and pragmatism

Own proposals and new business initiatives, defining technical feasibility and communicating risks and tradeoffs clearly to clients

Define what AI systems should and should not attempt, setting realistic expectations and being upfront about limitations

Conduct technical reviews and architectural assessments to maintain high standards across projects and team

AI Development

Guide the design and delivery of RAG systems, agentic frameworks, and LLM-powered solutions that are robust enough for production

Lead the application of advanced prompt engineering techniques including instruction design, few-shot sets, structured outputs, and tool/agent prompts

Run feasibility assessments to choose the right approach for each problem: prompting, RAG, fine-tuning, or classical ML

Mentor engineers on end-to-end AI system design and production deployment practices

Evaluation and Quality

Design evaluation frameworks including LLM-a

Publicado: 5/9/2026

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