Principal Solutions Engineer, Enterprise

Scale AI Scale AI · Data AI · New York, NY +1 · Enterprise Sales

Principal Solutions Engineer at Scale AI, focusing on enterprise adoption and deployment of AI/LLM solutions. This role involves technical strategy, solution architecture, executive advisory, and cross-functional alignment to drive complex deals and influence product direction. The role is customer-facing and requires deep technical expertise in AI/ML systems.

What you'd actually do

  1. Own technical strategy and execution for the company’s most complex, high-value enterprise opportunities, acting as the ultimate arbiter of the “technical win”
  2. Serve as a trusted advisor to executive stakeholders (CTOs, Heads of AI, Engineering leaders), guiding long-term AI/LLM adoption strategies
  3. Architect and lead end-to-end solution design, from discovery through pilots and productionization, across ambiguous and evolving customer requirements
  4. Drive cross-functional alignment across Sales, Product, and Engineering to unblock critical technical and business challenges
  5. Define and shape large, multi-phase Scopes of Work, translating ambiguous customer problems into scalable, production-ready solutions

Skills

Required

  • Deep technical background with significant experience in customer-facing engineering roles (pre-sales, forward-deployed, or post-sales) at enterprise scale
  • Proven track record of owning and closing complex, multi-stakeholder technical deals with Fortune 500 or equivalent enterprises
  • Strong systems thinking and architecture experience across cloud, data, and AI/ML systems
  • Hands-on experience with programming languages such as Python, Java, or similar, with the ability to prototype and validate solutions when needed
  • Experience operating as a senior technical advisor to executive stakeholders, with strong presence and credibility
  • Demonstrated ability to navigate ambiguity, influence without authority, and drive alignment across diverse teams
  • Exceptional communication skills, with the ability to translate between business, product, and technical audiences
  • High degree of ownership, intellectual curiosity, and bias for action in fast-paced, ambiguous environments

Nice to have

  • Deep experience with Generative AI / LLM applications in enterprise environments
  • Background in forward-deployed engineering or building production-grade ML systems
  • Experience in regulated industries such as financial services, insurance, or healthcare

What the JD emphasized

  • complex, high-value enterprise opportunities
  • executive stakeholders
  • ambiguous and evolving customer requirements
  • complex, multi-stakeholder technical deals
  • navigate ambiguity
  • ambiguous environments

Other signals

  • customer-facing technical leadership
  • drive technical strategy
  • architect and lead end-to-end solution design
  • influence product roadmap
  • mentor and elevate other Solutions Engineers