Mistral AI

DevOps Engineer

• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.)
• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our customer-facing APIs and large training runs
• Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences
• Drive continuous improvement in infrastructure automation, deployment, and orchestration
• Collaborate with software engineers to develop and implement solutions that enable safe and reproducible model-training experiments
• Help build a cloud platform offering an abstraction layer between science, engineering and infrastructure
• Design and develop new workflows and tooling to improve the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.)
• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements
• Document processes and procedures to ensure consistency and knowledge sharing across the team
• Contribute to open-source projects, research publications, blog articles and conferences

Site Reliability Engineer

Artificial Intelligence

• Drive the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation.
• Partner with senior executives to design AI roadmaps and collaborate with the Applied AI team to deliver solutions in production.
• Ensure seamless transitions from presales to postsales, directly contributing to customer success.
• Lead executive-level workshops to identify business challenges and opportunities for AI improvements.
• Co-create AI adoption roadmaps with customers and collaborate with Account Executives to develop business cases.
• Architect end-to-end AI solutions and partner with the Applied AI team for successful deployment.
• Monitor key performance indicators tied to business outcomes and proactively identify expansion opportunities.

AI Deployment Strategist

Marketing

• Architect and design tailored 1:1 (bespoke), 1:few, and 1:many ABM frameworks specifically for highly regulated industries, including Public Sector, Defense, and Financial Services (FSI).
• Partner with Sales to map buying groups, technical influencers, and C-suite personas, designing personalized engagement paths for each.
• Build multi-channel account plans (digital, social, and offline) that align with regional GTM goals and long-term revenue targets.
• Collaborate with Product and Content teams to design high-value, account-specific messaging that addresses the unique pain points of strategic APAC prospects.
• Design and execute joint ABM activities where relevant with key partners to expand account reach.
• Partner with Sales teams to support account engagement and campaign follow-up.
• Prepare account-specific assets, messaging, and reports to support deal progression.
• Maintain constant feedback loops with Sales and Partnerships to refine account plans and optimize campaign performance.
• Execute high-velocity campaign activations designed to accelerate market entry, drive top-of-funnel demand, and establish a dominant brand presence in the region.
• Provide comprehensive field support to drive lead generation, brand awareness, and measurable market penetration across the APAC region.
• Lead on-the-ground execution for regional field events, ensuring premium brand representation, seamless logistics, and high-quality lead capture.
• Track ABM impact using metrics such as account penetration, pipeline velocity, and marketing-influenced revenue.
• Measure field success through executive meeting conversion rates and deal acceleration rather than just attendance volume.
• Manage CRM and marketing systems to ensure accurate attribution and high-quality account data.

Strategic Account Marketing Manager, APAC

Support Engineer

• Handle Level 2 Support: Manage complex customer issues on Intercom, including latences, errors (API issues), Fine tuning/batch jobs/features
• Ticket Escalation: Escalate technical, financial, or solution-specific issues to the relevant teams (Engineering, Finance, Solution)
• Knowledge Base Management: Build and update FAQs and knowledge resources to empower customer self-service
• Customer Communication: Provide clear, friendly, and proactive responses; follow up as needed,
• Process Optimization: Work with bot and human support to streamline responses and reduce ticket volume
• Customer Focus: Maintain a customer-centric approach, ensuring a positive and efficient experience, especially for mid-tier paying users.

Technical Support Expert

People Operations

• Oversee daily HR operations concerning employee inquiries to ensure prompt and effective responses.
• Coordinate employee benefits administration, including enrollment, changes, and inquiries.
• Coordinate visas for new hires and for teams' work trip abroad.
• Lead HR project with external vendors to deliver the best services to our Employees.
• Ensure legal compliance and mitigate the Company’s risk by having a basic understanding of relevant employment laws.
• Maintain employee handbooks.
• Ensure we are able to onboard our new joiners the best way; any information that is relevant to our HR systems, Office and Managers.
• Formalize contractual elements during all the employees’ journey (labor contracts, amendments, certificates).
• Take care of our HR information and tasks and update them each time it is needed.
• Prepare and process payroll for employees in the North America region to ensure our employees will be paid on time.
• Lead any process optimization initiatives (automation, providers benchmark, etc.).
• Explore, implement, and refine people-related projects, procedures, and best practices that reflect our values and foster a positive company culture.
• Process optimization: Continuously improve, document, and streamline HR processes to enhance efficiency and accuracy.
• Open new countries from an HR perspective, deploying employee benefits administration.

HR People Ops

Research Scientist

• Design and run large-scale simulation campaigns using domain-specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
• Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
• Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
• Collaborate closely with the collaborate with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
• Manage research projects and client communications with engineering teams

Applied Scientist, AI4Engineering

Manager

• Define and execute a comprehensive documentation strategy aligned with product roadmaps and business objectives.
• Develop a forward-looking vision for documentation, anticipating the needs of diverse audiences, including developers, enterprises, and researchers.
• Advocate for users in product and technical discussions.
• Recruit, mentor, and develop a team of technical writers.
• Prioritize documentation projects based on business impact and user feedback.
• Work closely with Product, Engineering, and Support to ensure documentation supports product development, onboarding, and customer success.
• Partner with Engineering to adopt a "docs-as-code" approach, embedding documentation early in the development lifecycle.
• Create and enforce guidelines for tone, structure, and accessibility across all documentation (APIs, SDKs, tutorials, release notes, FAQs, etc.).
• Deliver clear, precise, and adaptable content for technical and non-technical audiences.
• Stay updated on trends in technical documentation, including AI, localization, and UX writing.

Technical Documentation Manager

Performance Marketing

• Develop and implement demand generation strategies aligned with business objectives and revenue targets
• Plan, execute, and optimize multi-channel campaigns (email, webinars, content syndication, social media, paid media, and events)
• Drive top-of-funnel lead generation and implement nurturing programs to move prospects through the sales funnel
• Build and organize lead flow through website optimization (CTAs, landing pages, conversion paths)
• Manage campaign budgets and allocate resources effectively to maximize ROI
• Analyze campaign performance and use data-driven insights to optimize efforts
• Collaborate with Product Marketing to develop compelling content, offers, and messaging
• Coordinate with third-party agencies to execute content, events, and syndication programs
• Ensure consistent branding and positioning across all demand generation initiatives
• Own the demand gen tech stack: MarkOps platforms, ABM tools and marketing analytics tools.
• Stay current with the latest demand generation technologies and trends

Demand Generation Lead

Systems Engineer

• Operate and maintain large-scale Linux environments (bare metal, clusters, cloud)
• Monitor system health, troubleshoot incidents, and ensure high availability
• Support production and research workloads across multiple environments
• Help scale clusters toward hundreds to thousands of nodes
• Work on systems handling petabyte-scale storage
• Improve performance, reliability, and resource utilisation
• Automate operational tasks using tools like Python, Bash, Ansible, or Terraform
• Improve deployment, provisioning, and system lifecycle management
• Contribute to system design and architecture decisions
• Act as a bridge between users and infrastructure

Systems Engineer, HPC

• Lead executive-level workshops with public sector leaders to identify mission-critical challenges and opportunities where Mistral’s AI can drive step-change improvements.
• Co-create AI adoption roadmaps with government and institutional customers, articulating the “art of the possible” while addressing regulatory, ethical, and operational constraints.
• Collaborate with Account Executives to develop business cases, quantify ROI, and align solutions with public sector objectives—such as digital transformation, citizen services, and operational efficiency.
• Architect end-to-end AI solutions, integrating Mistral’s models and platform into public sector workflows and technical infrastructure.
• Partner with the Applied AI team to design, prototype, and deploy AI solutions in production, ensuring scalability, compliance, and public value.
• Own the execution of pilot projects and proofs-of-value, demonstrating the potential of our technology and paving the way for full-scale deployment in government and institutional settings.
• Serve as a trusted advisor to public sector customers, guiding their AI strategy and ensuring they maximize the value of their investment in Mistral.
• Monitor key performance indicators (KPIs) tied to both business and societal outcomes, and communicate progress to executive sponsors and political stakeholders.
• Proactively identify expansion opportunities within public sector accounts, building on initial successes to drive long-term partnerships.
• Act as the bridge between public sector customers and Mistral’s internal teams, synthesizing feedback to influence product and research roadmaps.
• Develop reusable assets, best practices, and playbooks to scale go-to-market efforts and ensure consistent delivery excellence in the public sector.

AI Deployment Strategist, Public Sector

AI Deployment Strategist – Defence

• Design and run large-scale simulation campaigns using domain-specific solvers (e.g. OpenFOAM, ANSYS, COMSOL, Abaqus)
• Run training of AI models on physics data, with rigorous evaluation of coverage, accuracy, and quality against industry validation standards
• Build tools and frameworks for automated dataset creation, simulation pipeline management, and model evaluation
• Develop agents and RAG that integrate LLMs with engineering simulation workflows
• Collaborate closely with the collaborate with the science/research team on training runs and diagnose failure modes arising from data gaps or architecture limitations
• Manage research projects and client communications with engineering teams

Applied Scientist / Research Engineer, AI4Engineering

Research Engineer

• Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools.
• Interface cutting-edge research with production: integrate checkpoints, streamline evaluation, and expose APIs.
• Conduct experiments on the latest deep-learning techniques (sparsified 70 B + runs, distributed training on thousands of GPUs).
• Design, implement and benchmark ML algorithms; write clear, efficient code in Python.
• Deliver prototypes that become production-grade components for Le Chat and our enterprise API.

Research Engineer, Data Infrastructure

• Balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems.
• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads.
• Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters.
• Operate systems and troubleshoot issues in production environments (interrupts, on-call responses, users admin, data extraction, infrastructure scaling, etc.).
• Implement and improve monitoring, alerting, and incident response systems to ensure optimal system performance and minimize downtime.
• Implement and maintain workflows and tools (CI/CD, containerization, orchestration, monitoring, logging and alerting systems) for both our client-facing APIs and large training runs.
• Participate occasionally in on-call rotations to respond to incidents and perform root cause analysis to prevent future occurrences.
• Drive continuous improvement in infrastructure automation, deployment, and orchestration using tools like Kubernetes, Flux, Terraform.
• Collaborate with AI/ML researchers to develop and implement solutions that enable safe and reproducible model-training experiments.
• Build a cloud-agnostic platform offering an abstraction layer between science and infrastructure.
• Design and develop new workflows and tooling to improve to the reliability, availability and performance of our systems (automation scripts, refactoring, new API-based features, web apps, dashboards, etc.).
• Collaborate with the security team to ensure infrastructure adheres to best security practices and compliance requirements.
• Document processes and procedures to ensure consistency and knowledge sharing across the team.
• Contribute to open-source projects, research publications, blog articles and conferences.

Backend Engineer

• Design, develop and maintain scalable, robust backend features and APIs using modern frameworks.
• Ensure high performance and reliability across our distributed systems.
• Contribute to systems powering inference, billing, AI tooling, observability, and developer experience.
• Design and implement efficient, secure and scalable architectures that support our fast-growing products.
• Collaborate with infrastructure teams on deployment, monitoring, and performance optimization.
• Write clean, maintainable and well-documented code.
• Participate in code reviews and contribute to technical standards and best practices.
• Collaborate with product managers, platform engineers, and AI/ML teams to design, build, and deliver scalable model-as-a-service solutions for developers and enterprise users.
• Partner with teams across AI Studio, Le Chat & Mistral Code to ensure consistent platform-wide experience.
• Tackle complex engineering challenges, from distributed systems to AI product integration.
• Stay up-to-date with new technologies (e.g., AI/LLM integration, observability, or backend frameworks) and bring them into production when relevant.

Site Reliability Engineer

AI Deployment Strategist

Strategic Account Marketing Manager, APAC

Technical Support Expert

HR People Ops

Applied Scientist, AI4Engineering

Technical Documentation Manager

Demand Generation Lead

Systems Engineer, HPC

AI Deployment Strategist, Public Sector

AI Deployment Strategist – Defence

Applied Scientist / Research Engineer, AI4Engineering

Research Engineer, Data Infrastructure

Site Reliability Engineer

Software Engineer, Backend