Anduril System Design Interview Questions

Anduril's system design interview questions ask you to model one component. Web-scale prompts are rare. The signature one is a radar tracker for a moving ship. Beside it, candidates report a data structure built from scratch, such as a doubly linked list, or a walk through a computer-vision or perception pipeline, and now and then a distributed-logging system. All of them reward clean object modeling, sound interfaces and honest failure handling over sharding and capacity math. This section is the design counterpart to the coding interview questions. For the full loop, see the Anduril interview process.

Anduril's design interview has little in common with the distributed, web-scale conversation you meet at a consumer-tech company. Nobody asks you to shard a database for a billion users or size a cache tier for a photo feed. You design a component of a centralized, mission-critical system. That means modeling a piece of real machinery in clean objects, picking the right data structures, and making it hold up under real-world constraints. Anduril's own Lattice developer docs show the same thinking from the platform side. The entities overview describes an entity as a data structure built from components, and a track as any entity tracked by an asset, such as an aircraft track from radar or sensors. People do walk in having drilled the wrong book. It shows inside the first ten minutes.

It's an easy mistake. The round straddles two skills most people prep separately. It carries the object modeling and data-structure work of a low-level design interview, and it borrows the domain reasoning of an embedded or robotics engineer. A common opening is thin on purpose. You're expected to drive. Ask what the component is responsible for, what talks to it, and what has to stay true when a sensor drops out or a message arrives late. The interviewer wants to watch you turn a vague physical problem into a sound object model, not hear a memorized reference architecture.

The Anduril angle

Drilling web-scale design is the classic wrong turn into this round. The reflexes that win a distributed-systems interview (capacity math, sharding, replication lag, a global cache tier) are close to noise here, and reaching for them tells the interviewer you prepped for a different round. Anduril builds autonomous systems. The hard part is modeling the physical world correctly and behaving predictably in real time, and fanning a request out to more machines barely comes into it. Put the hours into clean object boundaries and data structures that fit the access pattern. Learn the failure modes a sensor or a vehicle actually produces, too, because that's the vocabulary the room is listening for.

The system design questions Anduril asks

A few prompt families recur, and which one you draw tends to track your team. They reward the same core. Each entity needs a clear responsibility, the interfaces need to make sense, and the design has to say what happens when the real world misbehaves. Read the list below as the shape of the conversation. It isn't a script.

Model a physical component: Design a radar tracker for a moving ship. The signature Anduril prompt. Model the objects: a tower or sensor, the contacts it detects, the platform it rides on, and the frames of reference between them. Then define how they update as the ship moves. It's object modeling grounded in real geometry. There's no scaling exercise.
Build a data structure from scratch: Implement a doubly linked list, with insert, delete, and search. Pure low-level design. Get the node structure right, handle the head, tail, and middle as distinct cases, and keep the invariants intact through every operation. Clean edge-case handling is most of the score.
Reason through a pipeline: Walk through a computer-vision or perception pipeline. Less drawing, more explaining. Walk how raw sensor input becomes a classified object, stage by stage, and where latency, accuracy and dropped frames enter. Anduril's platform fuses many sensors into one picture, so this thinking sits close to the real work.
The occasional distributed one: Design a distributed logging system. The one prompt that looks like a standard scale question, and it is the exception. Handle it with the usual moves. Don't expect the whole round to live here unless the team is backend-heavy.

How to approach it

The prompt is vague on purpose, so don't draw yet. Pin down the component first. Working in the same order every time keeps you from freezing on the geometry or over-building the wrong thing, and it reads as someone who has designed real components before.

Clarify what the component does

Start with the job. Ask what this piece is responsible for, what feeds it, what consumes its output, and what has to stay true for the larger system to trust it. In a radar prompt, that's what counts as a contact, how often positions update, and what the component must never get wrong.

Model the entities

Name the objects and their responsibilities: a tracker, a track, a sensor, a platform, a coordinate frame. Give each one clear ownership of its data. Decide which relationships are containment, which are references, and which change over time. This is where a clean design and a tangle part ways.

Define the interfaces

Specify how the objects talk: what methods each exposes, what a caller can assume, and what stays hidden. Keep the boundaries narrow so a change in one place doesn't ripple everywhere. If the design would slot into a larger platform, say what it publishes and what it listens for.

Reason about constraints and failure

Finish on the real world. A sensor drops out, a message arrives late, two readings disagree, and the design has to say what happens in each case. Bound the timing where it matters, decide what degrades gracefully, and name the invariants you protect under load. On a mission-critical system this part carries the most weight.

The Anduril angle

Let the physics drive the model. The people who do well here reason from the thing itself. A radar contact has a position known only with some uncertainty, and that certainty decays if the sensor goes quiet. On a moving ship every measurement lands in a frame that is itself moving, so the design has to say which frame a number lives in. An autonomous vehicle can't pause to wait for a slow component, so late data needs a defined fallback. None of this needs an aerospace background. It needs the instinct to work out how the real system behaves and let that shape the objects, the interfaces and the edge cases, which is what a defense-systems team is testing for.

The senior-level exception, stated honestly

There is a real distributed thread at the top of the ladder. Know it's there, and don't over-prep it. Anduril's Lattice platform fuses data from many sensors into a single shared picture across a fleet, which is a genuinely distributed problem. Entity data has to move between nodes, conflicting tracks have to be resolved, and a link has to hold together over a contested network. Senior and backend-leaning loops can pull the conversation that way. For most candidates, and for almost every early-career loop, the round stays centered on component modeling. Weight your prep there. Aiming at a senior backend seat? Keep the distributed material as a lighter second layer.

Reads as strong at Anduril

Drives the thin prompt, asking what the component owns and what it talks to before drawing a single box
Models clear entities with well-owned data and sensible relationships, then narrow interfaces between them
Closes on failure modes: a dropped sensor, a late message, two readings that disagree, and what the system does about each
Reasons from the physical domain, letting geometry, timing, and uncertainty shape the objects
Handles the data-structure prompt with correct invariants and every edge case, head, tail, and middle

Reads as off-target

Reaches for sharding, cache tiers, and capacity math on a problem that is really about clean modeling
Jumps straight to boxes and arrows without pinning down what the component is responsible for
Leaves the object model vague, with entities that share data and interfaces that leak
Treats edge cases and failure as an afterthought once the happy path is drawn
Assumes the round is Lattice-scale distributed design and preps only the web-scale playbook

The one worked design in this section

One worked design carries this section, and it rehearses the whole approach on a real Anduril-shaped problem. You take a component from its job to its entities and interfaces, then through the constraints and failure modes of a mission-critical system. Do it once, properly. The same moves carry to whichever prompt family your loop lands on, from the radar tracker to the perception pipeline.

Design a Mission-Critical Component

The worked design for this section. A physical, real-time component goes from a vague prompt to a clean object model, sound interfaces and honest failure handling. An Anduril design round rewards that arc, and the reasoning carries to the other prompt families.

Common questions

Is the Anduril system design interview distributed systems?

Usually not. You design a component of a centralized, mission-critical system: a physical piece modeled in clean objects, built on the right data structures, that holds up under real-time constraints and failure. Prep built around sharding, caching and web-scale capacity aims at the wrong target. A distributed thread can appear in senior or backend-leaning loops, tied to the Lattice platform. It's the exception.

How do I prepare for Anduril system design?

Practice low-level and object-oriented design. Skip distributed web-scale design. Get comfortable turning a physical component into entities and interfaces. Build a data structure from scratch with every edge case handled, and reason about what happens when a sensor drops out or a message arrives late. Reason from the domain (sensors, radar, autonomy, vehicles) and let the real behavior shape the design. The worked design in this section walks the full approach from a thin prompt to a defensible model.

Key Takeaways

✓Anduril's design round asks you to design a component of a centralized, mission-critical system rather than a distributed, web-scale one, so prep built around sharding and capacity math aims at the wrong target.
✓The prompts recur in a few families: model a physical component like a radar tracker for a moving ship, build a data structure from scratch, or reason through a perception pipeline. The occasional distributed-logging prompt is the exception.
✓Use a repeatable order: clarify what the component does, model its entities, define the interfaces, then reason through constraints and failure modes. Driving the thin prompt is part of the score.
✓Reason from the physical domain. Let geometry, timing, and uncertainty from sensors, radar, and vehicles shape the objects, the interfaces, and the edge cases.
✓A real distributed thread exists at senior and backend-leaning levels, tied to the Lattice platform, but most loops stay centered on component modeling. Weight your prep accordingly.

Next up:Design a Mission-Critical Component