About Phonely

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.

About Phonely

Every day, billions of phone calls are made to businesses. AI will soon power the majority of them. Businesses need a way to build, simulate, integrate and deploy voice AI agents —we are building this.

To create AI voice agents that can truly match human performance, we need 99.999% reliability. We’ve achieved this by building fine-tuned LLMs, real-time monitoring, Zapier-like automation, and robust infrastructure that can scale instantly.

We are scaling quickly—**our company grew 22% week over week in YC**, finishing in the top 5% of companies by revenue in our batch, closed a seed round and haven’t stopped growing. We are now looking for a Senior Backend Engineer to join us in San Francisco (or willing to relocate) and help scale our infrastructure.

What You Will Do

• Build and scale real-time AI systems by designing and deploying highly scalable backend services.
• Optimize performance and reliability by improving logging, monitoring, and telemetry (Datadog or similar).
• Deploy and maintain AI systems in production with robust deployment pipelines and CI/CD automation.
• Work with LLMs and OpenAI APIs, especially asynchronous API handling.
• Improve system resilience through containerization (Docker, Kubernetes), distributed systems, and NoSQL databases.

Competencies

• 3+ years of experience running production systems and building deployment pipelines.
• Strong knowledge of Kubernetes, cloud infrastructure (GCP preferred), and CI/CD automation.
• Experience working with Python backend engineering, LLMs, and real-time AI systems.
• Ability to optimize for high availability, performance, and cost efficiency.
• Bonus: Experience in voice AI and/or hyper-growth startup environments.

Why Join Us?

“I worked for IBM for the past 10 years. I started working for Phonely 3 months ago and I could never imagine going back. The growth of this company since I joined has been insane—I feel like I’m living in a movie.”

Aidan Hallett - Founding Engineer

At Phonely, you'll be working on the future of AI voice technology solving problems that no humans have ever solved before and working on changing the way people answer the phone forever.

Tech Stack

• Core Technologies: Python, Next.js, TypeScript
• AI Tools: OpenAI, Llama 3, Anthropic, Speech-to-Text, Text-to-Speech
• Infrastructure: GCP, Kubernetes, Datadog

Who Should Apply

• You have experience working in high-growth startups and thrive in fast-paced environments.

• You take ownership and get things done without waiting for direction.

• You have a strong technical background and are eager to work on cutting-edge AI. \

• The idea of working 12 + and loving every minute of it sounds worth your time.

• You want to shape the future of real-time AI-powered voice interactions.

If this sounds like you, let’s talk. Apply now and help build the next generation of voice AI at Phonely.

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.