Vice President, Engineering

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA · Autonomous Science Platform

VP of Engineering to build and scale a unified platform for autonomous experimentation in AI Science Factories, integrating AI into lab science, automation, hardware, and systems engineering. Focus on strategy, execution, and talent for global expansion.

What you'd actually do

  1. Set the engineering roadmap for ASP Engineering, including objectives, risks, and platform priorities via collaboration with the Robotics, Software, Science, and Product teams.
  2. Define and drive a unified platform architecture across hardware, automation, and systems engineering, reducing one-off designs and enabling repeatable system deployment across sites
  3. Implement efficient processes for lifecycle, design controls, safety and compliance, change management, and deployment of autonomous laboratories to support rapid scaling without compromising system consistency
  4. Develop a repeatable deployment model for standing up global AI Science Factory sites with predictable performance and reliability
  5. Integrate AI into the engineering lifecycle to bolster engineering speed and quality, decision making, and continuous improvement

Skills

Required

  • engineering leadership
  • platform architecture
  • systems engineering
  • hardware engineering
  • automation engineering
  • lab automation
  • robotics integration
  • scheduling and orchestration
  • reliability engineering
  • capacity planning
  • AI/ML integration
  • complex engineering systems
  • people leadership
  • org leadership
  • recruiting
  • mentorship
  • inclusive cultures

Nice to have

  • multi-domain engineering excellence
  • cross-discipline engineering fluency
  • interface standards
  • lifecycle management
  • science fluency
  • LIMS integration
  • observability pipelines

What the JD emphasized

  • 15+ years building lab automation or relevant engineering systems
  • 10+ years leading managers and multi-disciplinary teams at scale
  • Proven track record scaling automated labs or manufacturing-like lab operations, including instrument and robot integration, scheduling and orchestration, reliability engineering, and capacity planning
  • Demonstrated experience integrating AI/ML into engineering, operations, and/or research environments
  • Experience building and standardizing complex engineering systems from early-stage, project-based environments into scalable, repeatable platforms

Other signals

  • AI integration in lab science
  • scaling AI Science Factories
  • autonomous experimentation platform