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Simile

Enterprise AI platform simulating human behavior

Deployment Strategist

Implementation & Technical Account ManagementUpdated on Nov 9
Full-time

About the Job

Requirements

  • Experience from enterprise AI or data product operators, strategy consultants or investors moving into technology, or product managers or engineers with customer-facing experience.
  • Thrives in ambiguous, early-stage environments and demonstrates resourcefulness and initiative.
  • Is detail-oriented, accountable, and reliable for teammates and customers.
  • Communicates exceptionally, builds trust quickly with senior stakeholders, and navigates complex relationships.
  • Can learn technical concepts quickly and explain them clearly, and is comfortable engaging with AI concepts such as evaluations, validation, and model behavior; coding is not required.
  • Is willing to travel for customer engagements.

Responsibilities

  • Own customer relationships by being responsive, attentive to details, and trusted to deliver.
  • Own enterprise customer engagements from the first call through full deployment and beyond.
  • Develop deep knowledge of the platform, including simulations, population modeling, evaluations, and validations, and apply it in customer conversations.
  • Bridge customer needs with product and modeling teams, ensuring insights from the field inform internal decisions.
  • Take on high-impact projects across the business, including customer acquisition, simulation quality, and future product development.

Desired Qualifications

  • Comfort building lightweight tools or automations, including scripts and no-code tools.
  • Familiarity with enterprise software deployments or business-to-business software-as-a-service.

About the Company

Simile

Enterprise AI platform simulating human behavior

Simile builds AI models that simulate human behavior to forecast how individuals and groups will respond to scenarios using generative agents grounded in real data. The platform runs simulations of events like product launches, policy changes, or earnings calls to support decision-making. It differentiates itself by grounding agents in hundreds of interviews and behavioral science, combining Stanford-backed research with enterprise-focused decision intelligence. Its goal is to help organizations test decisions and forecast outcomes before acting, reducing uncertainty in strategic planning.

Company size
51-200
Company stage
Late Stage VC
Total funding
$300M
Headquarters
Palo Alto, CA
Founded
2025

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