Enterprise Account Lead, Physical Sciences

Lila Sciences Lila Sciences · AI Frontier · One Charles Park, Cambridge, MA · Corporate Development

This role is for an Enterprise Account Lead focused on selling Lila Sciences' AI-driven platform for scientific superintelligence to Fortune 500 companies in the energy, chemicals, manufacturing, and materials sectors. The role involves building and managing an enterprise sales pipeline, leading complex sales cycles, and translating the company's AI and autonomous lab capabilities into signed contracts. While the company's platform is AI-driven, the role itself is primarily sales-focused, requiring technical depth and business acumen to engage with buyers and inform the product roadmap.

What you'd actually do

  1. Build, manage, and grow a high-quality pipeline against clear revenue targets, from opportunity identification and qualification through proposal, negotiation, and close.
  2. Lead complex, multi-stakeholder sales cycles across R&D, platform/technology, data/AI, and business leadership, coordinating internally to ensure tight execution and timely progress.
  3. Maintain accurate revenue forecasts and deal records, surfacing tradeoffs, priorities, and decisions for Lila's leadership team.
  4. Engage confidently with physical sciences buyers, speaking their language and helping customers understand where Lila fits in their R&D stack.
  5. Own a portfolio of strategic accounts end-to-end, building executive relationships and running account-level planning (whitespace, expansion, renewal).

Skills

Required

  • BS, MS, PhD, or equivalent experience in chemistry, materials, physics, chemical engineering, or adjacent fields.
  • 2-5+ years in a client-facing role where you owned outcomes for customers, across BD, enterprise sales, management consulting, customer success, or applied science (industrial, energy, or materials).
  • Comfortable in a fast-moving, highly technical, cross-functional environment where the sales process, materials, and role itself are still being shaped.
  • Strong written and verbal communication, able to translate technical depth into clear, customer-ready narratives for both R&D buyers and procurement teams.
  • Highly organized and execution-oriented, comfortable managing multiple live accounts in parallel with limited oversight.
  • Collaborative, low-ego working style, able to build trust quickly with PMs, scientists, engineers, and product leaders.
  • Hands-on use of AI tools in day-to-day workflows and curiosity about how AI and autonomous science will reshape physical science.

Nice to have

  • Working familiarity with AI/ML applied to physical sciences: property prediction, generative models for materials, Bayesian optimization, simulation-driven design.
  • Direct exposure to enterprise R&D buying cycles in chemicals, energy, materials, semiconductors, or industrial biotech.
  • Prior experience in frontier AI (SaaS, biotech, robotics, or data) selling into technical buyers.
  • Prior experience as a founder or early GTM/commercial hire helping define early processes, playbooks, and collateral.
  • A point of view on where AI is and is not useful in physical sciences R&D today.

What the JD emphasized

  • owned outcomes for customers
  • highly technical
  • highly organized and execution-oriented
  • comfortable managing multiple live accounts in parallel with limited oversight