Mistral AIFounding Team Lead Applied AI Engineering, South Korea
Mistral AI is hiring a Founding Team Lead Applied AI Engineering, South Korea in Seoul, South Korea. Level rates it ; you can apply on Mistral AI.
Level's read on this job
- Builds AI ●●●● is how Level rates this AI engineer role: the job is building AI systems.
- The posting mentions RAG, AI agents and fine tuning among its tools and skills.
- Level classes it as a lead role.
- Mistral AI has 234 other open roles on Level.
AI in this role
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 Job
Mistral AI is seeking a founding Head of Applied AI Engineering, to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.
The role is an integral part of our Applied AI Engineering team, which is dedicated to driving the successful deployment of Mistral AI products and building complex enterprises use-cases. They work hand-in-hand with customers from the pre-sale stage to post-implementation, ensuring our solutions meet and exceed client expectations.
In this role, you’ll lead customer relations involving multiple stakeholders (CEO/CTO, data scientists, and software engineers) and function as a key resource in externalizing our research in production settings.
What you will do
- Deliver as an IC the critical lines of codes of our complex projects, you’ll be hands-on and de-risk the critical parts of our complex projects. You’ll stay deeply involved in coding, reviewing, and optimizing AI solutions.
- Lead technical teams of Applied AI Engineers, providing mentorship, technical guidance, and best practices for deploying state-of-the-art GenAI applications across industries.
- Lead technical discussions during pre-sales, translating customer requirements into actionable solutions and communicating Mistral’s technological advantages to diverse stakeholders.
- Design and oversee the implementation of complex AI systems, including fine-tuning, RAG, agentic workflows, and custom LLM applications, ensuring alignment with Mistral’s product roadmap and open-source initiatives.
- Drive innovation by identifying emerging trends in AI, evaluating new tools and methodologies, and championing best practices for fine-tuning, inference, and deployment.
- Work closely with product managers, researchers, and engineers to ensure seamless integration of customer feedback into Mistral’s product development cycle.
About you
- You are fluent in English and Korean native
- You hold a PhD / master in AI / data science/ software or you’re self-made
- You have 10+ years as a technical individual contributor (data scientist or software engineer) on AI-based products
- You have experience in Fine Tuning LLMs, tackling advanced RAG or agentic use cases, OR
- You have strong technical coding skills in Python and TypeScript, and experience with front-end and backend frameworks such as React/ NextJS/ VueJS, and NodeJS
- You have deep understanding of concepts and algorithms underlying machine learning and LLMs
- You have a solid understanding of software development principles, including design patterns, data structures, and algorithms.
- You have a deep understanding of Cloud Infrastructure and how to deploy AI based products
- You have deployed or built products with large scale user based
- You hold strong communication skills with an ability to explain complex technical concepts in simple terms with technical and non-technical audiences
Ideally you have:
- Contributed to open-source projects in particular in the space of LLM
- Experience with LLM/GenAI models
- Experience as a hands-on CTO, VP Engineering, Director Engineering, Head of ML, Forward Deployed Engineering leadership, and related scopes
- Experience founding a startup or as a founding member of a fast growing startup
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
Founding Team Lead Applied AI Engineering, South Korea at Mistral AI rates 90 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
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
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: RAG, AI agents, and Fine-tuning. 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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