Applied AI Engineer

Slang

Software Engineering, Data Science · Full-time

New York, NY, USA

USD 217k-242k / year + Equity

Posted on Oct 31, 2026

You'll join Slang's Engineering team as our Applied AI Engineer, the person who turns foundation models into products that restaurants trust with their phones. This is not a research or model-training role. You'll work with hosted frontier models and open-weight alternatives, and our own stack to solve real product problems: choosing the right model for each job, designing prompt architectures that hold up across model versions, wiring up agents and tool calls, and proving with evaluation that every change makes the product better before it reaches a guest. When a caller asks for a table for four on Friday at 7, you're the reason the AI gets the date right, sounds like a great host, and knows when to hand off to a human.

You'll lead the work to put model calls behind clean interfaces, redesign prompts so they travel across providers, and build the evaluation and A/B testing machinery that lets us swap models with confidence instead of hope. You'll own this loop end to end: prototype, eval design, rollout, production monitoring, and the post-launch question of "is it actually working for restaurants?" You'll partner closely with backend and platform engineers, product managers, and conversation designers across our delivery pods, and you'll set the technical direction for applied AI across the team.

You'll report to our VP of Engineering, a leader with deep experience across engineering and product who cares about craft, directness, and shipping work that matters. Our stack runs on Google Cloud Platform and spans multiple languages; we pick the right tool for the job and don't require experience in any specific one. You'll join key ceremonies including daily standup at 1:00 PM ET, bi-weekly cycle planning, and weekly Show & Tell. The role is hybrid from New York City (3 days a week in our NYC office), working alongside a distributed team across the US and Brazil.

Why You Belong Here and How You Will Grow

We're AI Native: we don't just sell AI, we run on it. That means your work isn't a side experiment bolted onto a product; it's the product. Our engineering culture values pragmatic solutions, low ego, and quality as a form of respect for whoever builds on your work next. We test before we ship, we ask "why" before we commit, and we'd rather finish a few meaningful things than start many. You'll find teammates who share what they learn in Show & Tell and written design docs, and who treat a hard question from a colleague as a gift, not a threat (Humility Ability is a real value here).