Director/ Senior Director, Lab Platform Engineering
Lila Sciences · Cambridge, MA USA · San Francisco, CA USA · Alewife, Cambridge, MA
Bio & Science AIonsitedirector$232k–$390k
At a glance
Highlights
- Lead the platform behind Lila's AI Science Factory powering automated labs.
- Own strategy for a fleet of distributed lab sites coming online reliably.
- Build systems that every robot, instrument and lab workflow depends on.
What they offer
- Competitive base compensation with bonus potential
- Generous early-stage equity
- Medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with generous company holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits including bike share memberships
- Company-subsidized lunch program
Ideal candidate
Seasoned infrastructure leader who loves building teams and reliable platforms at scale. You thrive owning complex edge-to-cloud systems and partnering across robotics, science and operations to accelerate discovery.
Requirements
- 15+ years in software or infrastructure engineering, with 8+ years leading teams including managing managers or tech leads
- Track record building and scaling a platform or infrastructure organization from a small team upward
- Deep technical grounding in hybrid on-premises and cloud infrastructure, including Kubernetes operated at scale outside public cloud
- Experience operating production fleets against explicit reliability targets with ownership of on-call and incident practice
- Ownership of infrastructure budget, capacity planning, and vendor negotiation
- Proven cross-functional and executive partnership, including communicating technical tradeoffs to non-engineering leaders
- Demonstrated ability to hire and develop senior and principal-level engineers
Lab profile
About Lila Sciences
Building an autonomous science platform where AI, automation, and biology co-evolve for medicine and materials.
What they build
- Autonomous Science Platform
- AI-designed biologics validated in wet-lab
- Electro-optic materials and photonic devices
Known for
- Large-scale automated data generation
- High-throughput protein purification and analytics
- Protein design and BioML modeling
- Robotic orchestration and lab simulation
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