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Mistral is a full-stack AI company providing frontier models, developer tools, applications, and compute infrastructure. They partner with enterprises across finance, manufacturing, defense, healthcare, and the public sector to co-create customized AI systems.
As an AI Deployment Strategist focused on Physics, you will drive adoption and deployment of Mistral's AI solutions for industrial enterprises, working from strategic vision through production implementation. This role bridges business strategy, AI innovation, and hands-on deployment, ensuring customers achieve transformative outcomes.
Key responsibilities include:
**Strategic Discovery & Vision Setting**: Lead executive workshops to identify business challenges where Mistral's AI can drive step-change improvements. Co-create AI adoption roadmaps with customers, articulating the "art of the possible" and clear paths to value. Partner with Account Executives to develop business cases, quantify ROI, and align solutions with customer objectives.
**AI Solution Design & Deployment**: Architect end-to-end AI solutions integrating Mistral's models into customer workflows and technical infrastructure. Partner with the Applied AI team to design, prototype, and deploy solutions in production. Own pilots and proofs-of-value demonstrating technology potential.
**Value Realization & Customer Success**: Serve as trusted advisor guiding customer AI strategy. Monitor and communicate outcome-driven KPIs with executive sponsors. Identify expansion opportunities within accounts to drive long-term partnerships.
**Cross-Functional Collaboration**: Act as bridge between customers and Mistral's internal teams, synthesizing feedback to influence product roadmaps. Create reusable assets and best practices to scale go-to-market efforts. Travel 30–60% to foster client relationships and support on-site deployment.
**Physics/Industrial-Specific Work**: Translate industrial engineering challenges into AI use cases. Design hybrid AI-physics pipelines and validate against ground truth simulations. Navigate enterprise IT constraints including air-gapped environments and on-premise HPC clusters. Conduct hands-on workshops to upskill engineering teams on AI-assisted workflows.
Required qualifications: 2+ years in client-facing strategic and technical roles (data science consulting, value engineering, technical sales). Deep understanding of computational mechanics, numerical methods (FEM/CFD/DEM), or multi-physics simulation. Familiarity with industry tools (Ansys, COMSOL, OpenFOAM, SimScale). Degree in relevant scientific field (Computer Science, Data Science, Engineering). Solid AI/ML/Data Science foundations with credibility to advise technical and non-technical audiences. Hands-on experience building and deploying AI applications (Python, JavaScript). Strong business acumen, structured problem-solving, executive presence, and communication skills for VP/C-level stakeholders. Resilient, results-driven, comfortable leading through influence.
