AI Solution Architect (Client facing)

Marais Advisory; Argentina; Presencial; ARS 1.800.000 - 3.000.000; Jornada completa

Descripción de la vacante

Marais Advisory is seeking an AI Solution Architect to lead client engagements from discovery to deployment. You will work with client stakeholders to understand business problems and design AI systems that can be implemented.

The role bridges business requirements and engineering execution, requiring hands-on experience with LLMs (Claude), data platforms (Databricks, Snowflake), and cloud infra. Strong presentation and communication skills are essential.

Formación

• Design and ship production AI systems
• Translate architecture into executive-friendly decks
• Lead client discovery and define problem scope
• Design end-to-end AI architectures: agent design, data flows, integration architecture, platform selection
• Communicate architectures and recommendations to client executives with cost and EBITDA impact

Responsabilidades

• Lead technical discovery with client teams to define the problem and constraints
• Design end-to-end AI architectures, data flows, integration, and platform choices
• Write specs the engineering pod executes within the 3-3-3 methodology
• Present architectures and recommendations to executives with cost and EBITDA implications
• Guide the build through production, adapting design to real constraints

Conocimientos

AI system design

Client-facing

Presentation skills

Clear communicator

Public speaking

Herramientas

Claude

Databricks

Snowflake

Descripción del empleo

The AI Solution Architect is the client-facing lead on Marais Advisory engagements. You sit with client stakeholders to understand the business problem, design the AI system that solves it, and explain that design back to the client in terms they can act on. The role bridges business requirements and engineering execution, from the first discovery session through production deployment.

Responsibilities

• Lead technical discovery with client teams to define the problem, current workflows, data, and constraints
• Design end-to-end AI architectures: agent design, data flows, integration architecture, and platform selection
• Write the specs the engineering pod executes within the 3-3-3 methodology
• Communicate architectures and recommendations to client executives through clear, well-structured PowerPoint presentations, tying design choices to cost takeout, cycle-time compression, and EBITDA impact
• Guide the build through production, adjusting the design as real constraints emerge

Requirements

• A record of designing and shipping production AI systems
• Hands-on depth with LLM platforms such as Claude, data platforms such as Databricks and Snowflake, and cloud infrastructure
• Strong presentation skills: able to translate technical architecture into executive-ready PowerPoint decks and present them with confidence
• Clear communicator, equally at home at the whiteboard and in the codebase
• Consulting or private equity portfolio company experience at a large firm (McKinsey, BCG, Bain, Deloitte, Accenture, EY, etc.)