VP of Engineering

1 Week ago • All levels • $350,000 PA - $400,000 PA

Job Summary

Job Description

The VP of Engineering will lead the engineering function for the Enterprise product line, responsible for delivery, quality, performance, and roadmap execution. They will build and scale a global high-performing team, partnering with customers and the GTM team to translate business needs into scalable technical solutions. They will also collaborate with research, product, and delivery teams to drive full-stack solutions from prototyping to production deployments. This role involves shaping the long-term vision, managing and mentoring senior engineering leaders, and making tradeoffs across technical and business dimensions.
Must have:
  • Led engineering teams in high-growth environments, ideally in ML.
  • Comfortable working with enterprise executives and navigating complexity.
  • Scaled engineering organizations across geographies.
  • Operates with urgency and clarity, executing priorities.
  • Experience partnering with sales, delivery, and customer success teams.
  • Credibility and curiosity in core technical areas.

Job Details

AI is transforming how the world’s largest companies operate. At Scale, our mission is to accelerate the development of AI applications. For 8 years, Scale has powered breakthroughs in generative AI, defense, and autonomy. Following our Series F, we’ve continued doubling down on accelerating Fortune 100 enterprises build and deploy of AI agents that solve complex, real-world problems—through our Scale Generative AI Platform (SGP).

We’re looking for a VP of Engineering to lead this charge for our Enterprise business. This is a critical leadership role responsible for building and scaling a world-class engineering organization focused on delivering generative AI solutions that drive impact for some of the largest and most sophisticated companies in the world.

You’ll own the end-to-end engineering motion behind our enterprise deployments: shaping technical direction, partnering closely with go-to-market and delivery teams, and ensuring our platform evolves to power the demands of cutting-edge AI applications. You’ll lead with clarity, build with urgency, and grow with intention.

What you'll do:

  • Lead the engineering function for our Enterprise product line, responsible for delivery, quality, performance, and roadmap execution

  • Build and scale a global high-performing team, with an emphasis on initiative ownership and engineering excellence

  • Partner directly with Fortune 100 customers and the GTM team to translate business needs into scalable technical solutions

  • Collaborate with research, product, and delivery teams in the Enterprise business unit and across Scale to drive full-stack solutions—from prototyping to enterprise production deployments

  • Shape the long-term vision and org design of the Enterprise engineering team, aligned with business growth and product evolution

  • Manage and mentor senior engineering leaders and instill a culture of accountability, speed, and results

  • Make rigorous tradeoffs across technical and business dimensions, backed by financial insight and operational understanding

  • Represent engineering in cross-functional planning cycles, including headcount, budget, and strategic initiatives

We're looking for someone who:

  • Has a strong track record of leading engineering teams in high-growth environments, ideally in ML, infrastructure, or complex systems

  • Is comfortable working directly with enterprise executives and navigating the technical and operational complexity of large deployments

  • Has scaled engineering organizations across geographies and understands how to structure and evolve teams effectively

  • Operates with urgency and clarity—able to distill priorities and move teams from ambiguity to execution

  • Has experience partnering deeply with sales, delivery, and customer success teams

  • Is equally comfortable in the weeds and at the executive level; knows when to lead from the front and when to empower others

  • Brings credibility and curiosity in core technical areas—especially applied ML, infrastructure, or AI agent systems

 

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