Vice President, Engineering

Your Impact at LILA

As Lila scales its AI Science Factories globally, the VP of Engineering will create and sustain an engineering model for a unified, scalable platform for autonomous experimentation. This role will be responsible for defining and implementing that platform across hardware, automation, and systems engineering. This executive will own strategy, execution, and talent across Lila’s systems, hardware, and automation engineering. The role sits on the senior leadership team, reports directly to the Chief Autonomous Science Officer, and interfaces directly with Robotics, Software, Operations, and Science teams.

The VP Engineering will bring deep technical experience in automation of lab science, a track record of building and leading multi-disciplinary engineering organizations, mentorship practices that foster career development of engineers at all levels, and the judgment to balance near-term delivery with long-term platform development. This is a hands-on leadership role in a fast-moving environment, requiring brilliance and dynamism to realize autonomous experimentation across materials science, chemistry, and life science. The role requires engineering innovations to achieve an unprecedented depth of AI integration in lab science, which combined with aggressive scaling of Lila’s AI Science Factories (AISFs) will produce the highest degree of scientific intelligence on earth.

What You'll Be Building

• Set the engineering roadmap for ASP Engineering, including objectives, risks, and platform priorities via collaboration with the Robotics, Software, Science, and Product teams.
• Define and drive a unified platform architecture across hardware, automation, and systems engineering, reducing one-off designs and enabling repeatable system deployment across sites
• Establish system-level ownership of architecture, interfaces, and requirements to ensure consistent integration across all engineering domains
• 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
• Develop a repeatable deployment model for standing up global AI Science Factory sites with predictable performance and reliability
• Create a culture of mentorship that supports execution of the roadmap while fostering career development of engineers
• Partner with Robotics and Software to build, industrialize, and scale all-of-science autonomous labs with a focus on reliability, throughput, and quality
• Integrate AI into the engineering lifecycle to bolster engineering speed and quality, decision making, and continuous improvement
• Collaborate with Talent Acquisition to establish hiring practices that accelerate identification and onboarding of brilliant, culturally-aligned engineers
• Partner with AI Research, Software, Product, and Science to align platform capabilities with scientific and commercial priorities
• Develop and communicate clear prioritization frameworks across engineering initiatives; translate organizational feedback into actionable systems and process improvements
• Represent Engineering with executive stakeholders and external partners; communicate tradeoffs, progress, and impact clearly
• Partnering with external integrators, OEMs, and contractors to expand engineering capacity

What You’ll Need to Succeed

• 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
• Demonstrated ability to balance rapid experimentation with the introduction of structure required for scale
• Technical expertise across lab automation, controls/SCADA, and science instrumentation, including integration and co-development of robotics and software/data/compute platforms
• Strong people and org leadership: recruiting and developing exceptional managers and ICs; building inclusive, high-ownership cultures that scale
• Excellence in retaining cultural and technical excellence across multiple sites of lab automation innovation and build-outs

Bonus Points For

• Multi-domain engineering excellence (mechanical, controls, electrical, systems) and cross-discipline engineering fluency (robotics, software, computer)
• Experience defining interface standards across hardware, robotics, and software systems
• Experience standing up lifecycle management (e.g., PLM-lite, change control, commissioning frameworks) in fast-moving environments
• Multi-domain science fluency (materials science, chemistry, life science)
• 10+ years experience integrating LIMS, orchestration, schedulers, and reliability and observability pipelines in lab automation
• Experience managing stage-gate transitions from R&D to scaled operations across multiple sites