QA Engineer

QA Engineer

AI-Native Platform | Planning Pod | Raleigh, NC | In-person, full-time

About Planning Pod
Planning Pod is the operating system for the events industry. More than 1,200 event venues and planners run their bookings, clients, contracts, payments, and day-to-day operations on our platform. We have a proven product, a loyal customer base, and a profitable business.
We are now building an AI-native version of Planning Pod, designed from the ground up around what large language models make possible. Backed by our own cash flow and by Kirra Capital, we have the speed and ambition of a startup paired with an existing customer base, deep domain knowledge, and the runway to build the right product. We plan to roll this new platform out to our existing customers over the next 6 months.

About the Role
This role owns quality for our new AI-native platform. You will build our automated test suite, establish QA processes from the ground up, and set the bar for what "ready to ship" means. You will work directly with our CTO and the engineering team, and mentor a junior QA tester who will join shortly after you.
We expect this role to do more than test against requirements. You are the first user, advocating for our customer base, catching what others will not, and adding your own experience to the roadmap. Testing an AI-native product means testing LLM outputs, agent behavior, and prompt regressions in addition to traditional application quality, and you will help us define what good looks like.

Who Should Apply
This role is based in our Raleigh, NC office, full-time, in-person. We are building together, in the same room, and that matters to us. Do not apply unless you are willing and excited to come to the office every day you are working. We expect to move quickly and make mistakes, and you should be willing to take that same perspective, staying focused on results instead of process. We do not want egos. We take our work seriously but not ourselves. We believe work should be fun, engaging, and a key part of your life. Do not apply if you are looking for a paycheck or an easy 9-to-5. This role is for people who want to build something impactful and are willing to invest their time and energy into it.

Our Requirements
• 4-7 years of software QA experience with a strong automation background
• Proven experience building and maintaining automated test suites (Playwright, Cypress, Selenium, or similar)
• Comfort with TypeScript or JavaScript for test authoring (our stack is TypeScript / Next.js)
• Experience testing SaaS applications with real customers in production
• Interest in testing AI features (LLM outputs, agent behavior, evals, prompt regressions)
• Excellent writing and verbal communication
• Strong critical reasoning and attention to detail
• Driven, high-energy, positive, and optimistic
• Based in Raleigh, NC (or willing to relocate) and excited to work in-person, full-time, with the team

Your Responsibilities
• Build and maintain the automated regression test suite for our AI-native platform
• Establish QA processes and standards from the ground up
• Design eval frameworks and regression tests for AI-generated outputs and agent behavior
• Own release testing and rollout validation for the migration to our existing 1,200+ customers
• Investigate and troubleshoot bugs surfaced by engineers, customers, or the QA tester
• Mentor the junior QA tester and build our long-term QA capabilities
• Participate in agile development sprints and review specs with a QA lens before code is written

Why Planning Pod
• You will help launch a new AI-native platform to 1,200+ existing paying customers
• You will work directly with the CTO, the engineering team, and the CEO from day one
• Real end-to-end ownership from your first week
• Startup pace with the backing of a profitable business and Kirra Capital as an investor
• Competitive salary + performance incentives
• Healthcare, 401K match, and 15 vacation days growing to 20 with tenure
• A clear path to grow into a QA lead or test engineering role as the team and platform scale