Enterprise Account Lead, Life Sciences

We are seeking an Enterprise Account Lead, Life Sciences to define how top 20 pharma and leading biotech companies engage with the world's first platform for scientific superintelligence. You'll be a foundational member of the team responsible for building and scaling our enterprise sales organization and driving deal execution for Lila's AI-driven drug discovery and life sciences platform.

As a revenue-focused individual contributor, you'll own and grow a portion of our life sciences revenue pipeline, working across technical product, science, GTM, software, robotics, and Physical AI teams to translate our closed-loop AI and autonomous lab capabilities into signed enterprise contracts across target discovery, small molecule, and biologics. You'll lead deep, multi-stakeholder engagements with a portfolio of top 20 pharma accounts, and in parallel, open new doors across the biotech ecosystem to build a repeatable mid-market motion.

The role demands technical depth, business acumen, an entrepreneurial mindset, and customer-centricity, and it is intentionally shaped to grow with the person who takes it on. In year one, you will work across product and customer strategy, customer technical discovery, sales process design, and account leadership in one of the most technically demanding verticals in enterprise software.

• Build and grow a qualified pipeline against clear revenue targets, from lead generation through close, with accurate forecasts and deal records.
• Lead complex, multi-quarter sales cycles across discovery, translational, platform, data/AI, BD/licensing, and business stakeholders at top 20 pharma accounts.
• Own a portfolio of pharma accounts end-to-end, building executive relationships across R&D, BD/licensing, and IT, and running whitespace, expansion, and renewal planning.
• Open new doors across the biotech ecosystem, sourcing opportunities and shaping a repeatable mid-market motion as it matures.
• Partner with product, science, and leadership to scope high-value engagements, unblock technical inputs, and keep deals moving.
• Own technical RFI and DDQ response, routing scientific questions to internal experts and packaging customer-facing deliverables.
• Build and maintain the revenue CRM, BD tooling, and a repeatable GTM playbook including qualification criteria, battle cards, and proposal templates.

• BS, MS, PhD, or equivalent experience in biology, chemistry, biochemistry, bioengineering, or adjacent fields.
• 2-5+ years in a client-facing role where you owned outcomes for customers, across pharma BD or alliance management, life sciences strategy consulting, pharma-tech enterprise sales or pre-sales, customer success, or applied science.
• Comfortable in a fast-moving, technical, cross-functional environment where the process, materials, and role itself are still being shaped.
• Strong written and verbal communication paired with disciplined execution, comfortable managing multiple live accounts in parallel with limited oversight.
• Track record of carrying multi-quarter pursuits where momentum comes from sustained stakeholder orchestration and proof-of-value milestones.
• 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 life science.

• Working familiarity with AI/ML applied to life sciences: target identification, generative models for molecules and biologics, predictive ADMET, computational biology.
• Direct exposure to enterprise R&D buying cycles in pharma, biotech, diagnostics, or therapeutics.
• 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 life sciences R&D today.

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

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