GenAI Infrastructure Solution Architect – EMEA

Mistral; Paris; Sur place; EUR 90 000 - 130 000; Plein temps

Avantages offerts par ce poste

Health insurance

Meal vouchers

Transport allowance

Parental leave

Visa sponsorship

Coaching opportunities

Résumé du poste

Mistral AI in Paris is seeking an experienced AI Solutions Architect to drive adoption and scaling of GenAI for enterprise clients. This is a purely individual contributor role at the intersection of innovation and impact, guiding deployments and helping customers realize measurable value.

You will travel about 30–60% of the time and spend time at client offices, partnering with product and science teams to tailor solutions, deploy models, and ensure production readiness across cloud and on-prem

Qualifications

• Degree in Computer Science, Data Science, Engineering or equivalent.
• Experience deploying and managing AI-based products in production.
• Fluent in Python and experience with containerization technologies.

Responsabilités

• Deliver value to customers and guide discovery with Account Executives.
• Lead product deployment and tailor solutions to client requirements.
• Onboard customers and ensure best production setup from GPU stack to back-end and front-end interfaces.
• Define and track success metrics for the POC and project progress.
• Collaborate with product and science teams to deliver state-of-the-art AI solutions.

Connaissances

Python

DevOps

Customer facing

Project management

Stakeholder management

Sales qualification concepts

Adaptable

Formation

Degree in Computer Science, Data Science or Engineering

Outils

Docker

Kubernetes

CI/CD

AWS

Azure

GCP

Description du poste

Mistral AI in Paris is seeking an experienced AI Solutions Architect to drive adoption and scaling of GenAI for enterprise clients. This is a purely individual contributor role at the intersection of innovation and impact, guiding deployments and helping customers realize measurable value.

You will travel about 30–60% of the time and spend time at client offices, partnering with product and science teams to tailor solutions, deploy models, and ensure production readiness across cloud and on-prem