Vertex is hiring an AI Product Engineer to build production AI products for real enterprise workflows.
You’ll work end-to-end: learn the domain, talk to users, design the UX, build the full-stack app, integrate LLMs/GenAI, and ship products used by customers and internal teams. Think human-in-the-loop review, decision support, workflow automation, escalation flows, and AI-native interfaces beyond chat.
This is a high-ownership, high-visibility role for an early-career builder who has already shipped real things. We’re looking for 0–3 years of experience, strong product taste, full-stack ability, hands-on AI/LLM experience, and a portfolio of apps, demos, repos, or case studies.
I worked through this for a tax company. They had a huge pile of artifacts from tax questions worked up for clients. What we did is we "reverse engineered" the process of the questions that would lead to that tax memo and the research steps to find the sources and conclusions. It worked well and we were able to replicate the process which the SME's created these memos.
For a given tax question, could you come up with the same memo quoting the same sources and same conclusion?
You would think this would be obvious to everyone. Clearly Apple is prepping for a digital overlay on the real world. Also less UI interaction, more voice/AI interaction.
It does mention that, it calls that out specifically.
As you grow, it’s tempting to fix every issue using the ‘cowboy’ method. It’s fast. It’s efficient. It leads to good results. But the number of things that need a cowboy fix grow exponentially, and cowboy fixes only ever fix that one thing, while system fixes fix future issues too. As you adapt from cowboy to drone, it’s easy to skew too much to one side or the other. No matter how good your systems are, sometimes stuff just needs to get done pronto. But sometimes you need to take a step back and trust that the system you built will do its job, and trying to jump in to speed things up will only make everything worse.
We are hiring an AI Product Engineer to join the strategy team to use the latest and greatest in AI to push Vertex forward into an AI-first company.
If you want to test drive being a technical founder, have experience building the full stack of an AI product from 0 to 1, and want to make a dramatic impact on in a public company, please apply.
Do you mean you don't understand why American's would think that America has done incredible things, or do you not believe America has done incredible things?
Vertex is hiring an AI Product Engineer to build production AI products for real enterprise workflows.
You’ll work end-to-end: learn the domain, talk to users, design the UX, build the full-stack app, integrate LLMs/GenAI, and ship products used by customers and internal teams. Think human-in-the-loop review, decision support, workflow automation, escalation flows, and AI-native interfaces beyond chat.
This is a high-ownership, high-visibility role for an early-career builder who has already shipped real things. We’re looking for 0–3 years of experience, strong product taste, full-stack ability, hands-on AI/LLM experience, and a portfolio of apps, demos, repos, or case studies.
Bonus: React, Figma, enterprise SaaS/internal tools, workflow products, customer-facing work, or solo-shipped projects.
Apply here: https://vertexinc.wd1.myworkdayjobs.com/VertexInc/job/Remote... and email [email protected] mentioning hackernews