DescriptionWhat 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.
RequirementsWhat 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 ProcessOur 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.
CompensationThe 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.
