Openai·Software Engineer·Technical Phone Screen·Senior

SeniorPrefer not to say

May 2026

Summary

Got a coding round for a Software Engineer role at OpenAI that was basically a mini compiler/type-system problem. Not your typical leetcode grind, more like a design-plus-implementation hybrid that caught me off guard in a good way.

Questions Asked (2)

Implement a small type system for a toy language, including Node and Function classes with string formatting methods. Nodes can be primitives, generic type variables, or nested tuples. Functions have parameter types and a return type.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

I spent way too long on the to_str formatting for nested tuples before even touching the Function class.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the requirements and scope of the type system, then design a class hierarchy with Node as an abstract base and subclasses for primitives, type variables, and tuples. Implement Function to hold parameter and return types, and add string formatting methods that produce readable type expressions. Discuss trade-offs between simplicity and extensibility, and test with examples.

Pro tip: Emphasize that you're designing for extensibility and testability from the start—mention how you'd add new node types without modifying existing code (e.g., using the visitor pattern or polymorphism). This shows architectural maturity beyond just getting it working.

1. Clarify requirements and scope

Ask questions to understand the expected features: what primitives exist, how tuples nest, whether type variables have constraints, and how functions are represented. Confirm the output format for string representations.

2. Design class hierarchy

Define an abstract Node class with a toString method. Create subclasses: PrimitiveNode (e.g., int, string), TypeVariableNode (e.g., T), and TupleNode (holding a list of Nodes). Ensure each implements toString appropriately.

3. Implement Function class

Create a Function class with a list of parameter Nodes and a return Node. Implement toString to format as (param1, param2) -> returnType, handling nested types recursively.

4. Handle recursion and formatting

Ensure toString methods recursively call child nodes' toString, adding parentheses for tuples and commas between elements. Consider edge cases like empty tuples or functions with no parameters.

5. Test and discuss trade-offs

Write test cases for primitives, variables, nested tuples, and functions. Discuss trade-offs: simplicity vs. extensibility, using inheritance vs. composition, and potential future features like type checking.

Key Points to Mention

Use of polymorphism and recursion for string formatting
Design patterns like Composite for nested tuples and Visitor for extensibility
Trade-offs between a simple class hierarchy and a more flexible but complex design
Handling of edge cases such as empty tuples or functions with no parameters
Importance of clear string representations for debugging and user output
Potential for future extensions like type constraints or unification

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Given a Function with generic type variables in its parameter signature and a list of concrete argument types, implement a function that resolves the generics and returns the concrete return type. Must handle nested tuples, conflict detection when a generic is bound to two different types, and unresolved generics in the output.

Algorithms & Data StructuresSystem Design

Author's notes

This is where I started sweating.

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AI HintsAI Generated

Suggested Approach

Model the problem as a recursive unification task: traverse the function signature and argument types in parallel, maintaining a substitution map from generic variables to concrete types. At each step, unify types, detect conflicts, and handle nested tuples by recursing; finally, apply the substitution to the return type and report any unresolved generics.

Pro tip: Clarify upfront whether generics are invariant or covariant and how to handle unresolved generics (error vs. leave as generic), as this significantly affects the algorithm and shows you think about edge cases and API design.

1. Clarify requirements and edge cases

Ask about invariance, conflict handling, unresolved generics, and whether tuples can be nested arbitrarily. Confirm expected output format for errors.

2. Define data structures

Represent types as a tagged union (generic, concrete, tuple) and use a substitution map (dictionary) to bind generic variables to concrete types.

3. Implement recursive unification

Write a recursive function that takes a parameter type and an argument type, and updates the substitution map. Handle base cases (generic vs concrete, concrete vs concrete) and recursive case (tuple vs tuple).

4. Detect conflicts and unresolved generics

During unification, if a generic is already bound to a different type, raise a conflict error. After processing all arguments, check the return type for any generics not in the substitution map and report them as unresolved.

5. Apply substitution and return result

Recursively substitute all generics in the return type using the final substitution map, producing the concrete return type or an error if unresolved generics remain.

Key Points to Mention

Recursive traversal of nested tuples to handle arbitrary depth
Substitution map (environment) to track generic bindings
Conflict detection when a generic is bound to two different concrete types
Handling unresolved generics in the return type (error or leave as generic)
Type representation using a tagged union or algebraic data type
Complexity analysis: O(n) time where n is the size of the type structure

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.