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I joined Zenity because it’s a rare opportunity to help build the operational foundation for a new security category focused on securing AI. The team is operating at a high level and moving quickly to define how security works in a world of AI agents.
As a leader, I value ownership, collaboration, and high standards. Our team moves with urgency and holds a strong sense of accountability to the business. I’m looking for builders who communicate proactively, take ownership of problems, and drive solutions that create measurable impact.
We have a large and growing set of AI projects across the business and need someone who can own that work from conversation to production. You will work across Sales, Marketing, Field Engineering, and Partner functions, building AI-powered tools and systems that make the people around you faster and more effective. If you get energy from moving between a whiteboard conversation and a terminal window in the same afternoon, this role was built for you.
About Zenity
Zenity is the leader in AI Agent Security and the first company to bring an agent-centric security platform to market. As enterprises accelerate AI agent adoption, we are establishing the security framework for how AI agents are secured and governed at enterprise scale.We deliver full-lifecycle visibility, governance, detection, prevention, and response for AI agents from build time to runtime, across SaaS, home-grown platforms, and end-user devices.
Backed by $180M+ in total funding, including a $125M Series C led by Norwest, with participation from SoftBank Vision Fund 2 and Microsoft's M12, Zenity is trusted by Fortune 500 and Global 2000 enterprises worldwide.
Join us in shaping how AI agents are secured at enterprise scale.
What you'll do
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. This is not prototype-and-hand-off work.
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.
Requirements
What You've Done
You have built and deployed AI-powered applications or workflows in a real environment, beyond a demo. You can describe what you shipped, who used it, and what broke first.
You have hands-on experience with tools like Workato, HubSpot, Zapier, Claude Code, Vercel, AWS, or similar. No single tool is a requirement, but familiarity across this space matters.
You have led internal projects with multiple stakeholders and can describe how you handled competing priorities or shifting requirements mid-project.
You have conducted user interviews or gathered requirements directly from end users and used that input to define what to build.
You understand how to structure data and context for AI systems so outputs are consistent and reliable in production.
You have strong analytical skills and are comfortable using data to track performance and inform decisions.
You are highly motivated and take real ownership. You think long term and put the business and customers first.
You move fast and hold a high bar for your own work at the same time. You are comfortable with ambiguity.
You are a builder. You take genuine satisfaction in shipping things that are useful and that people actually use.
Interview Process
Our interview process is designed to be transparent, conversational, and focused on real-world experience.
Recruiter Screen (30 minutes) – Learn more about Zenity, the role, and how we work.
Hiring Manager Interview (45–60 minutes) – A deeper conversation about your background, experience building AI systems, and how you approach solving problems.
GTM RevOps Interview (45 minutes) – A discussion with a member of the GTM RevOps team about how AI systems and automation can support revenue teams and real business workflows.
Technical Interview (45 minutes) – A conversation focused on your technical skills, how you build and ship AI systems, and how you collaborate with technical and business teams.
Cross-Functional Peer Panel (45 minutes) – Meet with peers across GTM and engineering to discuss how you work across teams and approach real-world challenges.
Please note that the interview process may evolve slightly based on scheduling and team availability.
Compensation
The expected base salary range for this role is $150,000 – $190,000 depending on experience, skills, and location. In addition to base compensation, this role may be eligible for equity and performance-based incentives.