QA Engineer

There are billions of calls made every day which will soon be handled by AI. Today 70% of business customer support calls are outsourced to call centers and contact centers. These call centers are looking for a solution that they can build simulate, and deploy voice agents all in one platform. We are building this.

Through YC we grew at 22% week over week and went through demo day with the some of the top revenue in the batch. We already work with the largest contact centers in the world and are looking for people that want to build the future of AI phone support together.

At some point in the future, every business will answer their phone with voice AI. We are building the platform that makes it possible, and we’re making sure the experience of using it doesn’t suck.

Phonely builds conversational voice AI agents for high volume phone workflows. Our customers use us to qualify leads, book appointments, route calls, and resolve real customer conversations in production. We are growing fast and just getting started.

About the Role

We’re hiring a dedicated QA engineer. You’ll be the last set of eyes on a feature before it ships, responsible for testing what engineers build for both correctness and UI/UX quality.

A big part of this role is automating yourself out of the repetitive parts. You’ll be the primary owner of our automated end to end test suite and you’ll expand and maintain it as the product grows.

This is an early-career role with a lot of room to grow. You’re the first QA hire, which means you’re not inheriting a process, you’re building one. No specific prior experience is required.

What You’ll Do

• QA new features and bug fixes across Phonely’s product, testing happy paths, edge cases, regressions, and general UI/UX quality

• Build automated tests to cover every non-human part of your job

• Own, maintain, and expand our automated end to end test suite

• Reproduce bugs reported by customers and internal teams, then write them up clearly enough that an engineer can fix them without a follow-up call

• Push back when something isn’t good enough to ship

• Build the QA process from scratch as our first dedicated QA hire

What We’re Looking For

• Some experience building or testing software: QA, software engineering, solutions/FDE, or similar

• Enough technical depth to inspect logs, HTTP requests, and browser behavior, and the instinct to use AI to move faster doing it

• AI native. You reach for the model before you reach for the manual

• User empathy and real opinions. You’re the last touchpoint before a feature ships, so you need to notice when something is bad and have the chutzpah to say so

• A technical background. A degree in CS or engineering is preferred, or equivalent hands-on experience

• Significant overlap with North American working hours

Nice to Have

• Experience with Playwright, Cypress, or similar E2E frameworks

• Familiarity with CI/CD pipelines and running tests in them

• Any exposure to voice, telephony, or real-time systems

Why Join Phonely

We’re super cool. Our team is a group of ex-athletes, founders, and builders with low egos, and a high belief that life is not about taking the easy road, but challenging ourselves to find the most we can be. Working at Phonely feels like family, we eat most meals together as a team (the company pays for food), we go on runs, hikes and surf together when we’re not working. Also we rent out Airbnbs in cool places (Rocky Mountains, Costa Rica) for our annual offsite so you can still see the world while on the grind.

To achieve human-level performance with voice AI agents, we need 99.9% reliability across all verticals. Building a high-performing Voice AI solution requires a combination of key elements:

1. Voice AI Infrastructure: Develop robust systems that can handle real-time conversations seamlessly.
2. API Integrations: Connect with relevant software to ensure smooth interactions.
3. LLM Testing, Simulation, and Evaluation: Validate models under various conditions to ensure accuracy.
4. Performance Monitoring: Continuously track metrics to optimize system performance.
5. Countless Other Tasks: From scaling infrastructure to managing edge cases, achieving this level of reliability is no small feat.

We’ve brought all of these elements together in one place so enterprises can integrate reliable and accurate voice AI into their offerings in minutes, not months.

Interview Process

1. 15-min intro call

2. Deep dive on your experience with a member of the engineering team

3. Practical exercise: find the bugs in a live feature and write them up

4. Final conversation with leadership