Jobs in Cambridge, MA

About the role

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. 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.

What you'll bring

• 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.

Benefits