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Lila Sciences

AI-powered scientific discovery for medicines

Manager / Senior Technical Program Manager

Program ManagementConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of technical program management experience managing complex, multi-team programs in a fast-moving engineering environment.
  • Ability to design processes from scratch and operationalize them at scale.
  • Technical fluency with application programming interfaces, data models, schemas, and system integrations.
  • Experience managing cross-functional dependencies across engineering teams and scientific stakeholders.
  • Commitment to work from the Alewife (Cambridge, Massachusetts) or San Francisco office 3–5 days per week.

Responsibilities

  • Own end-to-end program management across Designs & Schemas, LIMS, Build & Order, Project Management, and ELN.
  • Align requirements, dependencies, and timelines on cross-cutting programs spanning life sciences, formulations, and chemistry.
  • Communicate scope, tradeoffs, risks, and timelines to technical and scientific stakeholders, resolving blockers early.
  • Partner with the Engineering Director to design, operationalize, and improve engineering processes at scale.
  • Scale agile practices across SSR, including Jira hygiene, sprint planning discipline, and backlog management.
  • Define release gates, support intake processes, and operational dashboards that drive continuous improvement.

Desired Qualifications

  • Background in biology, chemistry, materials science, or another experimental science.
  • Experience with LIMS, ELNs, scientific registries, laboratory informatics, or scientific data platforms.
  • Experience modeling samples, protocols, lineage, provenance, or inventory.
  • Experience integrating scientific systems with automation or data infrastructure, including event-driven architectures.

About the Company

Lila Sciences

AI-powered scientific discovery for medicines

Lila.ai uses artificial intelligence to speed up scientific discovery in medicines and advanced materials. The system ingests large sets of scientific data, experimental results, and literature to identify patterns, generate hypotheses, and guide research programs. It differentiates itself by tackling deep scientific problems at scale and combining AI with domain expertise, rather than offering generic tools. The goal is to help humanity by delivering new medicines and materials that solve major biological and materials challenges through data-driven discovery.

Company size
501-1,000
Company stage
Series A
Total funding
$550M
Headquarters
Cambridge, MA
Founded
2024

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