Applied AI Engineer

Zenity•New York, NY

9h•$150,000 - $210,000

About The Position

Zenity is seeking an Applied AI Engineer to own AI projects end-to-end, from initial concept to production deployment. This role involves working across various departments such as Sales, Marketing, Field Engineering, and Partner functions to build AI-powered tools and systems that enhance efficiency. The ideal candidate is a builder who thrives in a fast-paced environment, enjoys moving between strategic conversations and technical implementation, and takes ownership of problems to drive measurable impact. Zenity is a leader in AI Agent Security, providing a platform for full-lifecycle visibility, governance, detection, prevention, and response for AI agents. The company is backed by significant funding and is trusted by Fortune 500 enterprises globally.

Requirements

Have built and deployed AI-powered applications or workflows in a real environment, beyond a demo.
Hands-on experience with tools like Workato, HubSpot, Zapier, Claude Code, Vercel, AWS, or similar.
Have led internal projects with multiple stakeholders and can describe how you handled competing priorities or shifting requirements mid-project.
Have conducted user interviews or gathered requirements directly from end users and used that input to define what to build.
Understand how to structure data and context for AI systems so outputs are consistent and reliable in production.
Strong analytical skills and are comfortable using data to track performance and inform decisions.
Highly motivated and take real ownership.
Think long term and put the business and customers first.
Move fast and hold a high bar for your own work at the same time.
Comfortable with ambiguity.
A builder who takes genuine satisfaction in shipping things that are useful and that people actually use.

Responsibilities

Own AI projects end to end, from the first conversation about a problem through to something that runs in production and gets used every day.
Work across GTM, ops, product, and strategy to identify where automation and AI workflows can remove friction and increase throughput.
Translate messy, half-documented internal processes into scoped specs and working systems, gathering requirements directly from the people doing the work.
Define new processes and tools to solve problems the business has not had to solve before.
Deploy AI applications using cloud infrastructure and integrate them into the GTM stack.
Work hand in hand with the hiring manager and GTM leadership to prioritize a large pipeline of AI projects and bring a point of view on what to build next and why.
Serve as a connector across teams, keeping complex initiatives on track and making sure execution matches intent.