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Salary: USD 192,000 - 238,000 / annual
You will own the Physical AI platform program—the shared infrastructure that powers Lila's autonomous labs. This is a high-leverage, influence-without-authority role spanning multiple engineering teams.
Key responsibilities include: driving the Physical AI platform roadmap with sequenced delivery and clear milestones; mapping and unblocking cross-team dependencies and critical paths; establishing and owning reliability and scalability programs (SLOs, launch readiness, capacity planning); maintaining a living risk register and driving incident follow-through; aligning dependent teams on scope and trade-offs; coordinating releases to ensure predictable launches; and raising operational rigor through status rituals, escalation paths, and decision records.
You'll need 4–8 years of technical program management for platform or infrastructure software across multiple teams. Core competencies include managing complex cross-team dependencies and multi-quarter programs, hands-on fluency with SLOs and release/incident processes, enough technical depth to engage backend and SRE engineers on real trade-offs, and proven ability to drive delivery across teams you don't manage. Clear communication bridging engineers and non-technical stakeholders is essential.
Bonus experience includes systems engineering and regulated-industry programs (aerospace, manufacturing, healthcare/life sciences), robotics or lab-automation context, SRE-adjacent depth (observability, on-call, incident management), or data-platform exposure (pipelines, capacity planning, ML/AI infrastructure).
Lila Sciences is building Scientific Superintelligence to solve major challenges by combining advanced AI models with proprietary AI Science Factory instruments into an operating system for science that executes the scientific method autonomously, accelerating discovery across medicine, materials, and energy.
