EliseAI

EliseAI

Solutions Engineer, Implementation & Delivery

New York City

Sponsorship not specified$135k-$185kDetected 69 days ago
SQLMachine LearningData VisualizationAgentic AIAccessibilityAccount ManagementCustomer Success

About the role

  • We're looking for a Solutions Engineer to join our presales and implementation team: someone who thrives at the intersection of technical depth, strategic thinking, and customer obsession.
  • You'll be embedded in our most complex, high-value enterprise engagements, partnering alongside Engagement Managers and Customer Success Managers to architect, configure, and activate EliseAI's platform for our most strategic customers.
  • The ideal candidate has worn multiple hats (Implementation Engineer, Technical Account Manager, Product Generalist) and brings a rare combination of hands-on technical ability, cross-vertical curiosity, and a genuine passion for making customers successful.

Responsibilities

  • Own technical implementation end-to-end across enterprise accounts, from presales discovery through configuration, testing, and go-live
  • Drive technical discovery during pre-sales by mapping customer workflows, identifying configuration requirements, and translating them into actionable implementation plans
  • Build and present best practice recommendations tailored to each customer's operational model, advocating for configurations that drive adoption and outcomes
  • Develop and maintain expertise across multiple verticals, becoming a trusted advisor who understands the nuances of different customer segments and use cases

Requirements

  • 3+ years of experience in solutions engineering, implementation engineering, technical account management, or a closely related presales/post-sales technical role

Nice to have

  • comfortable with APIs, system integrations, data flows, and configuration-heavy platforms
  • SQL proficiency and familiarity with BI tools (e.g., Looker, Tableau) a plus
  • Strong technical foundation: comfortable with APIs, system integrations, data flows, and configuration-heavy platforms

Skills

  • Serve as the internal voice of the customer, synthesizing implementation learnings into actionable feedback for Product and Engineering
  • Proactively identify risks in customer deployments and take initiative to resolve them before they escalate

Compensation

  • The salary range for this role is $135,000 - $185,000.
  • In addition to base salary, this role includes a launch-based SPIFF program, providing additional earning opportunities tied directly to successful customer go-lives.
  • EliseAI offers a competitive total rewards package including base salary, variable compensation, equity, and a comprehensive benefits package.
  • Exact compensation is determined based on experience, skill level, location, and qualifications assessed during the interview process.
  • Please note that employment with EliseAI is on an "at-will" basis, which means that either the employee or the company may terminate the employment relationship at any time, with or without cause or notice.
  • Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Benefits

  • Equity in the company
  • Medical, Dental, and Vision premiums covered at 100%
  • Fully paid parental leave
  • Commuter benefits
  • Fitness & home services stipend
  • Unlimited vacation and paid holidays
  • EliseAI offers a competitive total rewards package including base salary, variable compensation, equity, and a comprehensive benefits package.

Company info

  • Partner closely with Engagement Managers and Customer Success Managers to deliver a seamless, coordinated experience for complex, multi-stakeholder enterprise customers
  • Proven track record of owning technical implementation for enterprise-grade customers, ideally in a SaaS or AI/ML-driven product environment
  • In addition to meaningful work and real growth opportunity, we offer:

This listing is sourced directly from EliseAI's careers page and normalized into a canonical job model.