Sales Engineer, AI Infrastructure (SF)

Lavendo partners with startups and high‑growth companies to help them hire top‑tier sales, GTM, and technical talent. This role is with one of our clients; we’ll share full details about the company and interview process as we get to know you and confirm mutual fit.

About the Company

Our client builds the data layer that AI agents run on. One API call turns any URL into clean, structured, LLM-ready data. It's already the default way a huge number of developers pull web data into their AI systems, with over 1.5 million users building on the platform.

The numbers back it up: 8 figures in ARR in year one, more than doubled that in year two, and 180,000+ GitHub stars, putting them in the top 50 repositories of all time. They just closed a $75M Series B to build out a new knowledge library product for AI agents. The company is small, moving fast, and hiring people who want to build the next chapter with them.

The Mission

They believe developers and AI agents shouldn't have to fight the web to get data out of it. Every hour spent maintaining a scraper or babysitting a parser is an hour taken away from the actual product. Their job is to make that problem disappear.

The Opportunity

As a Sales Engineer, you'll own the technical side of every serious deal: discovery, architecture, demo, POC, start to finish. You'll sit close to the VPs and the founders, so the feedback loop between "customer needs this" and "we're building it" is short. The split runs roughly half pre-sales, half implementation. You see a deal through from the first call to production.

What You'll Do

• Run the full technical sales cycle: discovery, solution architecture, live demos, POCs

• Get in front of customers and show them, hands-on, how the product solves their problem

• Build POCs and technical proposals strong enough to turn "interesting" into "signed"

• Answer the hard technical questions that decide deals, and know when to pull in engineering

• Take what you hear from prospects straight back to product and engineering

• Split your time close to 50/50 between pre-sales and implementation

• Report to the VP of Revenue and Success, with real access to the founders

What You Bring

• 3-7 years in pre-sales engineering or solutions engineering at a dev tools, API, or data infra company, as an individual contributor

• Built and delivered POCs for enterprise prospects on your own

• Hands-on experience building with LLMs, RAG, agents, or AI data pipelines. You can read code, write, and use an API without help

• Can talk to an engineer about architecture and to a VP about ROI in the same afternoon

• Genuine energy for customer conversations, with real ownership over deal outcomes

• Authorized to work in the US already (no visa sponsorship on this one, so US citizens or Green Card holders)

Key Success Drivers

The people who do well here build things themselves. They get more energy from a good customer conversation than from a status meeting, and they're comfortable owning an outcome without a playbook to follow.

Why Join?

• Compensation & Equity: Base $143K–$199K, OTE $190K–$265K, 75/25 split. Meaningful equity in a fast-growing, well-funded startup.

• Traction: 8 figures in ARR in year one, more than doubled in year two. 180,000+ GitHub stars, putting them in the top 50 repositories of all time. A developer base of over 1.5 million users showing up before you even start selling to them.

• Funding: Just closed a $75M Series B. The new capital is funding a major new knowledge library product for AI agents.

• Team: ~40 people total, real visibility with the founders and leadership. No layers, no committees, fast decisions, short feedback loops.

• Benefits: 100% employer-paid medical, dental, and vision (50% for spouse and kids); employer-paid life, short-term, and long-term disability insurance; 401(k), pre-tax FSA, and commuter benefits; pet insurance; 15+ days PTO; 12 weeks fully paid parental leave for moms and dads; $100/month wellness stipend; $1,000/year learning and development budget; 3-month paid sabbatical after 4 years; team offsites twice a year; SF HQ perks and a loaner e-bike for commuting.

• Visa: not open to visa sponsorship on this one (US citizens and Green Card holders only).

Interviewing Process

• Recruiter Screen: confirm a shipped AI-native project (public repo preferred) and a closed deal you can size, with your role in it

• Intro Chat (25 min): what you've been working on, why this caught your interest, what you want next

• Technical Chat (60 min): a real scenario from the business, discovery, demo, or scoping a POC for a hard prospect problem

• Paid Work Trial (1–2 weeks): remote-friendly, working an actual technical deal scenario with the team

We are proud to be an equal opportunity workplace and consider all qualified applicants without regard to race, color, religion, national origin, age, sex, marital status, ancestry, disability, genetic information, veteran or military status, gender identity or expression, sexual orientation, or any other characteristic protected by law.