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
Embedded directly in the product Team, you will build the evaluation and A/B testing framework, add end-to-end observability, and run a reliable model release process. Work with Science to ship measurable improvements to quality, latency, safety, and reliability
What you will do
• Build and maintain an LLM evaluation framework (reference tests, heuristics, model-graded checks).
• Define and track metrics: task success, helpfulness, hallucination proxies, safety flags, latency/cost.
• Run A/B tests for prompts, models, and system prompts, analyze results, recommend rollout or rollback.
• Set up observability for LLM calls: structured logging, tracing, dashboards, alerts.
• Operate the model release: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection.
• Improve core behaviors: memory write/retrieve policies and evals, intent classification, follow-ups, routing, tool-call reliability.
• Create templates and docs so other teams can author evals and ship safely.
• Partner with Science, diagnose regressions and lead post-mortems.
About you
• Strong TypeScript or Python skills
• Production LLM experience: prompts, tool/function calling, and system prompts.
• Hands-on with evals and A/B testing, you can design metrics and make rollout decisions from data.
• Observability: logging, tracing, dashboards, alerting
• Product mindset: form hypotheses, run experiments, interpret results, iterate.
• Clear written and spoken communication, autonomous; and product-oriented.
Now it would be ideal if you have experience with
• Safety systems: moderation, PII handling/redaction, guardrails.
• Release operations: canary/shadowing, automated rollbacks, experiment platforms.
Hiring Process
• Introduction call - 30 min
• Hiring Manager interview - 30 min
• Technical Rounds
- Live-coding Interview - 45 min
- AI Engineering Interview - 45 min
• Culture-fit discussion - 30 min
• References
