Applied AI Engineer, Prototyping

The Proto Team is the technical pre-sales arm of the GTM organization. We operate at the intersection of product and customer, translating what Mistral’s technology can do into real-world solutions that deliver value fast.

We work across three core areas:

1. Deliver for customers: Build high-impact solutions on short timelines that prove value, unlock deals, and generate follow-on revenue.
2. Ship for Mistral internally: Build full-stack applications that unblock teams across procurement, legal, and sales, applying the same engineering rigor to internal needs.
3. Drive product innovation: Act as the product’s reality check. We test early, validate real use cases, push systems to their limits, and both improve and build the product itself.

As an Applied AI Engineer in the Proto Team, you operate as a technical lead building production-grade AI systems in 4 to 8 weeks.

You work across GTM, engineering, and applied AI, translating ambiguous business problems into working software.

You own architecture, make technical decisions, and ship full-stack systems end to end.

You work directly with customers and internal teams, moving from scoping to deployment with high autonomy and high velocity.

You also sit close to the product loop: testing new capabilities, pushing systems to their limits, and turning real-world usage into product direction.

This role is for fast-moving, highly curious builders who thrive in complexity and ambiguity. You move across domains quickly, ramp on new industries fast, and build with a strong hacker mindset and deep engineering instincts.

• →Build and deliver full-stack AI solutions for global customers, owning the end-to-end execution from scoping to deployment as technical lead.
• →Engage directly with customers to understand use cases, define requirements, and translate them into robust technical architectures and working systems.
• →Collaborate across GTM, product, and engineering to ship solutions and contribute to internal tools, product improvements, and open-source initiatives.
• →Solve complex applied AI problems across industries, working on real-world GenAI use cases and providing hands-on technical guidance throughout engagements.

• Fluent in English.
• Thrive in ambiguous, fast-paced environments with a strong problem-solving mindset, focused on building robust and scalable solutions.
• A builder at heart, balancing speed with precision and taking a methodical approach to technical execution.
• Strong communication skills, able to explain complex technical concepts to both technical and non-technical audiences.
• Client-focused, with a strong interest in innovation, new technologies, and improving existing systems.
• Comfortable collaborating across diverse teams and translating client needs into clear, actionable technical plans.

• 2+ years experience as a hands-on engineer shipping AI-powered products (ML, software, or full-stack).
• Strong track record of building and deploying production systems end to end, not just prototypes.
• Comfortable working across the modern AI stack: LLMs, RAG, agentic systems, and their deployment in real-world applications.
• Strong software engineering fundamentals in Python, with experience building scalable backend systems (e.g., FastAPI, Pydantic).
• Working understanding of frontend development (e.g., React or Vue) to build usable interfaces when needed.
• Broad technical range: able to move fluidly between system design, infrastructure (e.g., Kubernetes), and applied LLM problem-solving, with a strong bias toward shipping.

• Built or won hackathons / AI competitions, with a track record of shipping creative solutions under tight deadlines.
• Experience with Docker, Kubernetes, cloud platforms (AWS or GCP), and infrastructure tooling such as Terraform.
• Contributed to open-source projects, ideally in the LLM or applied AI space.
• Strong full-stack + AI experience, having built and shipped end-to-end applications (e.g., FastAPI, Next.js).