About Mistral

At Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.

We democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.

We are a dynamic, collaborative team passionate about AI and its potential to transform society.
Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.

Join us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.

Role summary

Mistral is looking for a Security Platform Engineer to architect and maintain the infrastructure ensuring the observability of our production systems.

You will treat the SIEM and logging infrastructure as a high-performance data product. Your objective is to ensure the reliability, scalability, and cost-efficiency of the pipelines ingesting security telemetry from our GPU clusters, cloud environments, and applications.

What you will do

• Own the set-up, lifecycle, availability, and performance of the SIEM solution, ensuring 99.9% uptime for log ingestion and query availability.
• Design and maintain high-throughput data pipelines to collect, buffer, and transport logs from distributed systems to the SIEM.
• Implement parsing logic and schema standardization to ensure unstructured logs are searchable and actionable for analysts.
• Manage alert rules, connectors, and dashboard configurations, avoiding manual console configuration ("Click Ops").
• Analyze ingestion patterns to identify noisy, low-value data. Implement filtering and aggregation at the source to maximize signal-to-noise ratio.
• Architect data tiers to balance query performance with compliance retention requirements and cloud costs.

About you

• 5+ years of experience in Site Reliability Engineering (SRE), Data Engineering, or Security Engineering with a focus on logging infrastructure.
• Deep understanding of log management challenges at scale (indexing strategies, sharding, partitioning, throughput tuning).
• Strong experience deploying and monitoring stateful workloads on Kubernetes and Cloud providers (Azure/GCP) and On-Prem.
• Ability to write production-grade Python or Go for automation and custom log exporters.
• Experience managing monitoring, alerting, and on-call rotations for critical infrastructure.

Hiring Process

• Introduction call - 30 min
• Hiring Manager interview - 30 min
• Technical Rounds I - 45 min
• Technical Rounds II - 60 min
• Culture-fit discussion - 30 min
• References