AI Engineer, Product

About Mistral

Mistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems—across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector—co-creating customized AI systems that they can run on their terms.

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 Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.

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 .

Role summary

Embedded directly in a product team as search, chat, documents, or audio, you'll improve AI-powered features through rigorous evaluation, prompt and orchestration design, and rapid experimentation. You'll own your domain's AI quality end-to-end: define what "good" looks like, measure it, run experiments, and ship what works. Work with Science to deliver measurable improvements to quality, latency, safety, and reliability.

What you will do

• Design and run evaluations for your product area: reference tests, heuristics, model-graded checks tailored to search relevance, chat quality, document understanding, or audio performance.

• Define and track metrics that matter: task success, helpfulness, hallucination proxies, safety flags, latency, cost.

• Own prompt and orchestration design: write, test, and iterate on prompts and system prompts as a core part of your work.

• Run A/B tests on prompts, models, and configurations; analyze results; make rollout or rollback decisions from data.

• Set up observability for LLM calls: structured logging, tracing, dashboards, alerts.

• Operate model releases: canary and shadow traffic, sign-offs, SLO-based rollback criteria, regression detection.

• Improve core behaviors in your product area, whether that's memory policies, intent classification, routing, tool-call reliability, or retrieval quality.

• Create templates and documentation so other teams can author evals and ship safely.

• Partner with Science to diagnose regressions and lead post-mortems.

About you

• 3-4 years of experience; backgrounds that fit well include ML engineers moving closer to product, or software engineers with real AI/ML production experience.

• Strong TypeScript or Python skills - we have both tracks depending on team fit.

• Production LLM experience: prompts, tool/function calling, system prompts.

• Hands-on with evals and A/B testing; you can design metrics, not just run them.

• Comfortable implementing directly in product code, not only notebooks.

• Observability experience: logging, tracing, dashboards, alerting.

• Product mindset: form hypotheses, run experiments, interpret results, ship.

• Clear communication, autonomous, and oriented toward production impact over experimentation for its own sake.

It would be ideal if you also have:

• Safety systems experience: moderation, PII handling/redaction, guardrails.

• Release operations: canary/shadowing, automated rollbacks, experiment platforms.

• Prior work on search ranking, chat systems, document AI, or audio ML features.

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

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Location & Remote

The position is based in our Paris HQ offices and we encourage going to the office as much as we can (at least 3 days per week) to create bonds and smooth communication. Our remote policy aims to provide flexibility, improve work-life balance and increase productivity. Each manager can decide the amount of days worked remotely based on autonomy and a specific context (e.g. more flexibility can occur during summer). In any case, employees are expected to maintain regular communication with their teams and be available during core working hours.

What we offer

Competitive salary and equity package

‍⚕️ Health insurance

Transportation allowance

Sport allowance

Meal vouchers

Private pension plan

Generous parental leave policy

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What we offer

We offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.

For the most up-to-date details on benefits available in your location, please refer to our Benefits page .

Privacy Policy

Your privacy matters to us. You can learn more about how we handle your personal data in our Applicant Privacy Policy .