Liquid AI

Spun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.

We have early enterprise traction and a product that solves real problems for technical buyers. What we don't have yet is a repeatable commercial engine. This is one of our first sales hires, and you will own the full sales cycle: prospecting through close, selling Liquid Foundation Models to technical leaders at enterprises across consumer electronics, automotive, life sciences, and financial services. You'll work directly with our founders and GTM leadership to shape pricing, packaging, and deal strategy while building the playbook the team scales on.

We need someone who:

• Is obsessed with selling: Not management, not BD, not player-coach. We need someone energized by running deals, with meaningful revenue closed, and the drive to keep doing it, where every deal matters.

• Knows the AI landscape: You've recently sold AI/ML infrastructure, developer tools, or platform products. You understand how technical buyers evaluate model performance, latency, and deployment tradeoffs. This context is non-negotiable at our stage.

• Has deep empathy: We value sellers who build trust through a genuine understanding of prospects, their business, and their challenges. Listening more than talking. Earning credibility through curiosity, not pressure.

• Thrives in the building phase: Our playbook does not exist yet. We see that as the appeal, not the risk. You've built a process while hitting a number before, and you want to do it again at a company where the commercial motion is yours to define.

• Own the full sales cycle from prospecting and outbound through negotiation, close, and handoff

• Build and manage a qualified pipeline across target verticals, using modern outbound tools and your own network to increase deal velocity

• Lead discovery calls, product demos, and technical deep-dives with our engineering team, including proof-of-concept evaluations and benchmarking cycles

• Navigate complex enterprise procurement across legal, security, and technical evaluation stakeholders

• Partner with founders on pricing, packaging, and deal structures for enterprise engagements

• Feed frontline market intelligence back to product and leadership: objections, competitor signals, pricing feedback, and use-case trends

• Build our sales playbook: document what works, create repeatable processes, and lay the foundation for scaling the GTM team

Must-have:

• Recent experience selling at an AI company (currently or within the last 2 years), with demonstrated ability to hold credible technical conversations with CTOs, VPs of Engineering, and Heads of AI/ML

• 5+ years of closing experience in B2B software sales with a track record of meeting or exceeding quota

• Experience building a pipeline through a combination of self-sourced outbound, network-driven leads, and inbound qualification

• Prior experience at a Series A-C startup or early-stage environment building the sales motion, not just running an existing one

• Comfort with consultative, longer-cycle enterprise sales involving multiple stakeholders, technical evaluations, and complex procurement

Nice-to-have:

• Experience selling into consumer electronics, automotive, life sciences, or financial services verticals

• Familiarity with ML concepts: model training, fine-tuning, inference, and on-device deployment

• Proficiency with modern outbound and pipeline tools

• Existing relationships with technical decision-makers at target enterprise accounts

• Closed net new revenue from self-sourced and self-managed deals, directly contributing to our B2B revenue targets

• Our sales playbook exists and works: qualification criteria, pricing frameworks, objection handling, and handoff processes are documented so the next hire can use them on day one

• GTM leadership relies on this hire's judgment for deal strategy, pricing, and pipeline prioritization

• Build our commercial engine: This role shapes how Liquid AI sells, not inheriting someone else's playbook. The work directly determines whether our technology reaches the market.

• Compensation: Competitive base salary + variable compensation with equity in a unicorn-stage company

• Health: We pay 100% of medical, dental, and vision premiums for employees and dependents

• Financial: 401(k) matching up to 4% of base pay

• Time Off: Unlimited PTO plus company-wide Refill Days throughout the year