AI Deployment Strategist, Industrial Engineering / Physics , APAC

Mistral provides full-stack AI solutions, from frontier models to developer tools, applications, and compute. As an AI Deployment Strategist, AI4Eng for Physics and Engineering in APAC, you are Mistral's forward-deployed operator on strategic enterprise accounts across automotive, aerospace, semiconductors, industrial equipment, and energy. You own the delivery of AI solutions for physics and engineering challenges end-to-end.

Responsibilities

Run technical discovery sessions to understand business and engineering requirements; Identify, qualify, and prioritize use cases aligned with the customer's strategic R&D and product-development challenges; Translate business goals into a concrete AI roadmap and high-level solution architecture, validating feasibility with Product and Applied AI teams; Build ROI models and business value propositions, and own scoping documents and SOW inputs; Own end-to-end delivery: discovery, design, build, deploy, adoption; Set up the account operating model: governance, decision forums, and cadence; Drive day-to-day execution: priorities, milestones, unblockers, and risk management; Drive scope control and change management, ensuring the right artifacts are produced (design doc, runbook, eval plan, rollout plan, handover); Bring knowledge of processes and regulations from the industries served (aerospace, semiconductor, automotive, industrial equipment, energy); Lead user testing, training, change management, and developer enablement; Track value realization against agreed KPIs and report to executive sponsors; Capture field learnings and feed product gaps and platform needs back to Product, Science, and Engineering; Support pre-sales motions

Requirements

Advanced university degree in physics or engineering, or IT; 5+ years of experience as a (technical) project manager in a relevant industry, e.g., automotive, semiconductors, or aerospace; Experience in software development and machine learning; Hands-on coding proficiency (Python at minimum), with the ability to read design docs and hold deep technical conversations with data scientists, ML engineers, and simulation engineers; Strong grasp of where AI creates value in computational science: surrogate models, PDE solvers, FEM/CFD acceleration, inverse problems, and differentiable simulation; Familiarity with deployment patterns (SaaS, VPC, on-prem, hybrid) and security and compliance basics; Strong communication skills with the ability to explain complex technical concepts in simple terms and to manage C-level stakeholders

Nice to have

Experience in numerical simulations for physics and engineering (CAE, CFD, FEM, DEM, etc.); Ideally agile project management methodologies

Benefits

Healthcare coverage; Parental leave; Retirement plans; Relocation support; Wellness programs; Meal and transportation allowances; Other location-specific perks (vary by country)