Applied AI Engineer, Site Reliability Engineer - EMEA
Mistral AI is hiring an Applied AI Engineer, Site Reliability Engineer - EMEA for a remote role open to applicants in France. Level rates it ; you can apply on Mistral AI.
Level's read on this job
- On Level's scale, this AI engineer role is Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include Kubernetes, Terraform and Prometheus.
- Level classifies it as a senior role.
- Level lists 234 other open roles at Mistral AI.
AI in this role
Build and operate reliability frameworks and infrastructure for enterprise-grade applied AI solutions.
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 the team
The Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact.
Our team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. Our SRE team works transversally across customer engagements, enabling value creation through Mistral tech - at scale. By joining the team you will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision.
About The Job
You will be one of the founding engineers of the Applied AI SRE sub-team.
Your mission, alongside the team, is to build and operate the framework to ensure Mistral’s solution delivery is reliable and sustainable - and applied uniformly across all our accounts, both Mistral-hosted and customer-hosted. You should already have a strong understanding of what operational excellence looks like, and you’re ready to scale your impact.
You will operate in four concurrent modes:
- BUILD - Design for a fleet of Mistral platforms and apps. Build proactivity to reduce reactivity.
Productize reliability, author runbooks, create SLO templates, implement observability.
- RUN - Operate the Tier-1 customer environments that Mistral are contracted to operate.
Ensure SLO compliance, own on-call and incident response, manage drift, partner with Technical Support as L3 escalation, champion high signal post-mortems.
- ENABLE - Productize how Mistral deploy, secure, and scale our Applied AI solutions.
Engineer on-demand provisioning, author security baseline packages, embed security guardrails, automate everything.
- SECURE - Own the security operations layer for our customer-side deployments.
Lead CVE response across the fleet, ship supply-chain integrity controls (SBOM, signed images, provenance), co-page with InfoSec on security incidents, enforce secure-config baselines.
This is a framework-first, fleet management role at heart. If you're excited by the difference between solving one customer's problem and structurally solving the class of problem for every customer, this is the role.
How We Work in Applied AI
• We care about people and outputs.
• What matters is what you ship, not the time you spend on it
• Bureaucracy is where urgency goes to vanish. You talk to whoever you need to talk to. The best idea wins, whether it comes from a principal engineer or someone in their first week.
• Always ask why. The best solutions come from deep understanding, not from copying what worked before
• We say what we mean. Feedback is direct, timely, and given because we care.
• No politics. Low ego, high standards.
• We embrace an unstructured environment and find joy in it.
About you
• Fluent in English.
• 5+ years in SRE, Production Engineering, or DevOps, with a record of shipping tooling.
• Strong multi-tenant Kubernetes fluency, namespace segmentation, network policy, RBAC, admission control, operations at scale.
• On-call discipline: incident response, blameless post-mortem culture, runbook-first mindset.
• Observability stack in production: Prometheus, Grafana, OpenTelemetry, Loki, Tempo, Signoz.
• Infrastructure as code: Terraform, Ansible (or close equivalents).
• Proficient in Python and/or Golang for tooling and automation.
• Security mindset: you treat secure-SDLC, CVE response, and supply-chain integrity as reliability properties of the shipped artifact, not as someone else's job.
• Strong written communication skills: runbooks, post-mortems, and customer-facing incident comms are core deliverables of this role.
• Comfortable operating with high autonomy in an ambiguous, fast-paced environment — and disciplined enough to defend the team's scope when work tries to spill in.
• Solid Linux internals, networking debug, and distributed-systems fundamentals.
Strong plus
• Cloud or application security background (AppSec, K8s security, supply chain — SBOM, cosign, SLSA). At least one of our early hires must bring this; if it's you, flag it.
• Experience operating LLM / model-serving stacks in production
• Experience with multi-cloud or on-prem hybrid customer environments (AWS, GCP, Azure, sovereign clouds).
• Open-source contributions, particularly in SRE, observability, or security tooling.
By applying, you agree to our Applicant Privacy Policy.
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.
How we rate this
Applied AI Engineer, Site Reliability Engineer - EMEA at Mistral AI rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI engineer jobs at this level
Pay
- Typical AI engineer job
- $184k
This posting doesn't list pay. Use the typical AI engineer figure when pay comes up. See AI engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where site reliability engineering was part of your work. What did you do?
- Tell me about a project where infrastructure was part of your work. What did you do?
- Tell me about a project where observability was part of your work. What did you do?
- Tell me about a project where ai systems was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: AI Research, Site Reliability Engineering, Infrastructure, Observability, and AI Systems. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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