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Retell

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Retell (Retell AI) is a startup that provides a platform for building, testing, and deploying AI-powered voice agents for phone calls and customer interactions. It is known for enabling businesses to automate voice communications using conversational AI.

2 interview notes · updated Jul 2026

Retell·Software Engineer·Onsite - System Design / Architecture

Jun 2026
Retell SWE interview that was basically 'build a mini SQL engine from scratch.' Three parts: architecture, core implementation, then keep extending it as the interviewer piles on features. More open-ended than I expected, less about grinding leetcode and more about whether you can scope a real system under pressure.
  • Design and implement a small in-memory SQL query engine that takes a SQL string and executes it against in-memory tables. Start with a basic subset and be ready to extend as features get added.
  • Before writing any code, walk through the architecture of the query engine. What are the components, what does each consume and produce, and where do future features like JOIN or GROUP BY plug in?
  • Implement the core engine: parse and execute SELECT with a WHERE clause supporting comparison operators and AND/OR logic.
  • Extend the engine to support ORDER BY and LIMIT, aggregate functions with GROUP BY, and an INNER JOIN between two tables.
  • How would you support joining three or more tables, and how does join order affect performance?
  • How would you add HAVING and subqueries to your AST and executor?
  • Where would a query optimizer fit in your design, and what is one rewrite that would help performance?
  • How would you test this engine to stay confident it's correct as you keep adding features?

“The scoping part is what tripped me up at first.”

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Retell·Software Engineer·Onsite - System Design / Architecture

Apr 2026
System design round at Retell for a software engineer role. The whole thing was one big open-ended problem about designing a programmatic outbound calling platform, and they expected you to drive the conversation yourself rather than wait for prompts. Scale was clearly the part they cared most about.
  • Design an outbound calling platform end to end: how does an enterprise API request turn into a phone call, how do you track call state, and how does the system hold up under load?
  • A burst of thousands of call requests arrives in seconds from multiple enterprise customers. How do you keep the platform stable, respect carrier concurrency and per-second rate limits, and stay fair across tenants?
  • How do you enforce a per-carrier concurrency budget across a distributed fleet of dialer workers without over-dialing?
  • A carrier starts showing elevated failure rates and high latency. How does the system detect this and reroute traffic without causing a retry storm?
  • How do you handle retries safely so a client retrying a failed API call never results in the same phone number being dialed twice?
  • How would you support scheduled calls and calling-window compliance, for example never dialing a recipient before 9am in their local timezone?
  • What happens on the answered leg of the call, and what new scaling constraints does bridging to a real-time AI voice agent introduce?

“This is the core question and it's basically a full system design in one prompt.”

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