Founding Engineering Lead

The Role

We're looking for a Founding Engineering Lead who is both the commando shipping the first version of hard things and a strategist on some of the most interesting applied AI problems in enterprise software.

You'll own technical architecture end to end while sharing in the product roadmap and ML strategy alongside the founders - which means following the research closely enough to argue about what applies to a system acting on live revenue and what's still hand-waving.

The shape of the week changes. Call it 75% building and 25% leading over a year, but expect the mix to swing. You'll be leading a pod of three to four engineers, including their growth and performance, and you'll still be the one shipping.

What You’ll Do

• Technical lead on new initiatives, spearheading initial designs and builds vs. reviewing someone else’s.
• Own the architecture behind our core platform. You make the build-versus-buy and infrastructure cost calls.
• Set the engineering bar for a team where agents write most of the code. Review standards, definition of done, release cadence, on-call.
• Lead the pod. Sprint scope and sequencing, unblocking, growth and performance conversations, and hiring the engineers who come next.
• Shape technical direction with our CTO. Product roadmap, ML approach, model strategy.

What You’ll Bring

• You work at the frontier of agent-driven development. You've built your own setup rather than living on the defaults, and you keep finding ways to get more out of agents than they give most people.
• 5+ years of engineering experience, ideally including time as a technical founder, founding engineer, or staff IC who led a pod at a place with a high bar.
• You were the primary author on something that shipped in the last six months, and owned delivery end-to-end with little oversight to catch your failures.
• You've been accountable for other engineers' output as a tech lead, pod lead, or manager.
• Applied ML judgment, both classical (you know which technique fits which data, and you catch a bad validation design before anyone points at it) and frontier (informed opinions on transformers, world models, and can argue on ML applications)
• High tolerance for ambiguity, inherited code, and unglamorous work. Based in NYC, excited to be in-office.