Senior Technical Program Manager, Robotics

• Drive the Physical AI Platform roadmap: sequence delivery across teams, with clear milestones and owners.
• Coordinate cross-team dependencies: map the critical path, surface blockers, and unblock work before it slips.
• Own reliability & scalability programs: stand up SLOs, launch-readiness reviews, and capacity planning.
• Track risk end to end: maintain a living risk register and drive incident follow-through to closure.
• Align stakeholders: keep the teams who depend on the platform current on scope and trade-offs.
• Coordinate releases: run release and change coordination so launches are predictable.
• Raise operational rigor: establish the rituals - status, escalation paths, decision records - that keep delivery honest.

• Platform program management: 4-8 years of technical program management for platform or infrastructure software across multiple teams.
• Dependency & risk mastery: managing cross-team dependencies, critical paths, and risk registers on multi-quarter programs.
• Reliability fluency: hands-on with SLOs, launch readiness, capacity planning, or release/incident processes.
• Technical credibility: enough depth to engage backend, platform/SRE, and QA engineers on real trade-offs.
• Influence without authority: proven ability to drive delivery and hard decisions across teams you don’t manage.
• Clear communication: you translate fluidly between engineers and non-technical stakeholders.

Bonus Points For

• Systems engineering & regulated-industry programs: a systems-thinking background and program experience in regulated, safety-critical domains - aerospace, manufacturing, or healthcare/life sciences. Exposure to validation/V&V regimes (GAMP 5 / FDA CSA, DO-178C) or enterprise-to-shop-floor integration (ISA-95) a plus.
• Scientific or lab-automation context: robotics, hardware-in-the-loop, or lab/scientific computing environments.
• SRE-adjacent depth: observability, on-call, and incident management practice.
• Data-platform exposure: programs spanning data pipelines, capacity/cost planning, or ML/AI infrastructure.

Lila Sciences is building Scientific Superintelligence to solve humankind’s greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you’d love to work in, even if you don’t meet every qualification listed above, we encourage you to apply.