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Mistral AI

Open-weight LLMs and enterprise AI deployment

Enterprise Success Manager

Account ManagementUpdated on Nov 14
Full-timeNo salary listedHybrid

About the Job

Requirements

  • At least 5 years of experience in customer-facing roles such as Customer Success, Delivery/Implementation, or Solutions Consulting, ideally in a technical AI or SaaS environment.
  • Experience owning outcomes for enterprise customers of technical products or deployed solutions, including adoption and commercial outcomes such as retention, renewal, and expansion.
  • Strong technical fluency in enterprise deployment models, including understanding how on-premises, VPC, and serverless deployments affect available features, telemetry, upgrades, and security reviews, and validating details with technical teams.
  • Ability to engage credibly with architects, engineers, IT, and security teams and translate technical trade-offs into clear business implications for executives and users, while recognizing when to involve a deeper technical expert.
  • Ability to create structure or improve processes in ambiguous, fast-moving environments and to build without waiting for detailed direction.
  • Ability to align teams without formal authority, surface risks early, and drive decisions through to completion.
  • Ability to define meaningful success metrics, assess customer health, and carry renewal and NRR accountability.
  • Fluency in English.

Responsibilities

  • Build a clear view of each account’s objectives, stakeholders, deployed use cases, commitments, and risks, and translate it into a shared success plan with owners, milestones, and measurable outcomes.
  • Establish an operating cadence with customer sponsors, business owners, IT, and delivery teams, and lead success reviews that clarify progress, risks, decisions, and next steps.
  • Define baselines and track outcomes for each use case, including adoption and usage against entitled seats, customer satisfaction, operational health, and business impact, and turn the evidence into a value narrative.
  • Understand how each customer’s on-premises, VPC, or serverless deployment model affects the products and use cases they can access, operate, and scale, validating specifics with technical teams.
  • Identify practical implications of deployment choices, including security and data requirements, access and integrations, release and upgrade cadence, available features, capacity, observability, and support processes, and explain trade-offs to customer and Mistral stakeholders.
  • Translate deployment constraints into an adoption plan, aligning enablement and release communications with the customer’s running version, accounting for security approvals and upgrade windows, and agreeing how to measure usage when telemetry is limited.
  • Spot risks early, qualify their impact on adoption, renewal, or value, and coordinate the appropriate Solutions, Product, Engineering, or Support owners to resolve them; set expectations without making unvalidated technical or roadmap commitments.
  • Help customer teams move from a delivered use case to regular, effective use by identifying users, workflows, and change-management needs.
  • Coordinate onboarding, training, product updates, and hands-on enablement with Mistral and customer teams; develop customer champions and train-the-trainer motions to scale adoption beyond direct Mistral involvement.
  • Prepare the transition from delivery to run by clarifying operational ownership, support and escalation paths, and resources users need to succeed independently.
  • Monitor adoption and customer health, investigate shortfalls in usage or value, and lead a coordinated plan to address their causes.
  • Own renewal motions by tracking renewal dates and auto-renewal versus non-auto-renewal terms, assessing renewal risks, and starting renewal work early.
  • Track and improve account NRR, identify new use cases, teams, and expansion opportunities, and share value-grounded opportunities with the account team.
  • Lead business reviews with the account team covering delivered value, owned risks, needed decisions, and roadmap requests.
  • Gather and qualify feedback from users, technical teams, and sponsors; distinguish enablement needs from product gaps, deployment constraints, and support issues, and route each to the appropriate owner.
  • Track important customer requests and communicate progress and limitations, while Product and Engineering retain ownership of product and technical decisions.
  • Create and refine reusable playbooks, success plans, handover practices, and measurement approaches by testing them with customers.
  • Identify what needs to happen, make a plan, mobilize the right people, and follow through without waiting for a perfect process or detailed instructions.
  • Spend roughly one-fifth of the time in protected, rotating build time for creating and improving company practices and materials.

Desired Qualifications

  • Professional French is strongly preferred.
  • Experience with AI, machine learning, data platforms, or complex enterprise software, including production deployments in regulated or security-sensitive environments.
  • Experience working alongside deployment, engineering, or professional services teams on custom use cases and the transition from implementation to ongoing operation.
  • Experience building adoption, change-management, or customer education programs across large organizations.
  • Experience at a forward-deployed, solutions-led company.

About the Company

Mistral AI

Open-weight LLMs and enterprise AI deployment

Mistral AI builds open-weight large language models and the tools to run them, along with inference infrastructure and enterprise products that let organizations deploy AI with control over data residency, customization, and the underlying stack. Its platform provides open-model architectures and a deployment stack for inference, governance, and integration that can run on‑premises or in the cloud. This openness and modular stack differentiate it from single-vendor hyperscalers by prioritizing data locality and flexibility. The company aims to enable reliable, customizable AI deployment at scale for businesses and public-sector customers across many countries.

Company size
1,001-5,000
Company stage
Series D
Total funding
$7.2B
Headquarters
Paris, France
Founded
2023

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