Interview guides · Aeva

Aeva Software Engineer Interview Guide

Aeva Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

As a Software Engineer at Aeva, you are at the forefront of next-generation sensing technology. You will be instrumental in developing the software that powers Aeva’s unique 4D LiDAR-on-chip technology, which is transforming how autonomous vehicles, consumer electronics, and industrial robotics perceive the world. Your work directly impacts the precision, efficiency, and reliability of real-time data processing systems that define the future of machine perception. This role requires a blend of high-level systems thinking and rigorous implementation. Whether you are working on Digital Signal Processing (DSP), State Estimation, or Perception Algorithms, you will be solving complex, real-world problems that move beyond standard software engineering.

This guide is scoped to a Software Engineer candidate at Aeva.

Focus areas

Coding Proficiency in C++
DSP (Digital Signal Processing)
Data Structures & Algorithms (DSA)

The Aeva interview process

Aeva candidates report 3 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial conversation with a recruiter to assess your background and fit for the role.

What to demonstrate

Initial conversation with a recruiter to assess your background and fit for the role
Depth in Coding Proficiency in C++

How to prepare

Be able to walk your CV end to end in two minutes, and say why this company specifically.
Have your salary expectations, notice period and location constraints ready, and ask for the rest of the loop in writing.

Hiring Manager Conversation

Discussion with a hiring manager or director about your background and interest in Aeva.

What to demonstrate

Discussion with a hiring manager or director about your background and interest in Aeva
Depth in Coding Proficiency in C++

How to prepare

Prepare two projects you led end to end, each with the decision you owned and what it cost.
Have three questions about the team's roadmap and how success is measured in the first six months.

Technical Assessment

One-on-one sessions with team members focusing on your domain expertise and problem-solving skills.

What to demonstrate

One-on-one sessions with team members focusing on your domain expertise and problem-solving skills
Depth in Coding Proficiency in C++

How to prepare

Answer aloud and timed: How do you approach Lidar data validation and verification?
Answer aloud and timed: Walk me through a challenging bug you encountered in a production environment and how you resolved it.

Where candidates lose points

Own your expertise

If you list a skill on your resume, be ready to go deep. Interviewers will often probe the limits of your knowledge on your own projects.

Communicate your thought process

Never jump straight into writing code or sketching a design. Explain your assumptions and your approach first.

Prepare your own questions

Use the time at the end of the interview to ask about the team's current challenges or the company's technical roadmap. It shows genuine interest.

Research the technology

Understand what makes Aeva’s 4D LiDAR unique compared to traditional systems. Having this context will help you frame your technical answers more effectively.

Questions & practice

How do you optimize C++ code for performance and memory constraints?

Medium · Technical & Domain Knowledge

Approach

Say what the runtime actually does before reasoning about the code.
Name what is shared across threads and what owns each piece of state.
Identify the window where an invariant is briefly untrue.
Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

What happens if two callers reach this at the same time?
Where could this allocate more than you expect?

Walk me through a challenging bug you encountered in a production environment and how you resolved it.

Medium · Problem Solving & Algorithms

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Given a specific scenario, how would you prioritize computational resources between competing processes?

Medium · Problem Solving & Algorithms

Approach

Restate the input: its shape, its size, and what is guaranteed about it.
Name the brute-force solution and its complexity before improving on it.
Choose the data structure from the access pattern, not from familiarity.
State the target complexity and say which constraint rules the naive version out.

Follow-up

How does this change if the input no longer fits in memory?
What is the worst case, and how likely is it on real data?

Denormalise tenant onto revisions and backfill it live

Hard · denormalisation · online migration · backfill

resource_revision (revision_id, resource_id, version, actor_user_id, change_kind, patch, request_id, created_at) has 400M rows and no tenant column; tenant_id lives only on resource. Two reads need it: a tenant-scoped audit feed ordered by created_at DESC, and an offboarding purge. Both join back to resource today. Justify adding tenant_id to resource_revision against those two reads, name the anomaly the copy introduces and the constraint that prevents it, then give the ordered migration for a live table taking 1.2k writes/second — the lock each step takes, how the backfill is batched, and where each step stops being reversible. PostgreSQL 16.

Approach

Justify from the access path rather than from taste. Without the column, the audit feed either scans resource_revision by created_at and discards other tenants' rows, or resolves the tenant's resource_ids first and probes with them — both proportional to the tenant's whole history rather than to one page. With (tenant_id, created_at DESC, revision_id DESC) it is a seek that stops at 50 rows, and the purge becomes a ranged delete instead of a join.
Name the cost exactly: a second copy of a fact can disagree with the first. Make the disagreement unwritable rather than documented — add UNIQUE (resource_id, tenant_id) on resource so it can serve as a foreign-key target, then FOREIGN KEY (resource_id, tenant_id) REFERENCES resource (resource_id, tenant_id) on the revision table. A revision can then only ever carry its parent's tenant.
Step one, expand: ALTER TABLE resource_revision ADD COLUMN tenant_id BIGINT NULL, with no default, so it is a catalogue change and no rewrite. It still needs ACCESS EXCLUSIVE for an instant, and that instant queues behind the longest open transaction on the table while every later query queues behind it — set lock_timeout to 2s and retry rather than wait.
Step two, dual-write: deploy the writer that populates tenant_id on every new revision while reads still use the join. Reversible by redeploying the previous build, because nothing reads the column yet.

Follow-up

The backfill is half finished and a rollback is required. What state is the table in, and what does the previous build do with a half-populated column?
How do you verify the backfill actually finished, given rows are still being inserted while it runs?

Find version gaps and relay lag with window functions

Medium · window functions · event tables · frame semantics

outbox_event holds event_id, aggregate_type, aggregate_id, aggregate_version, event_type, payload, status ('pending','published','dead'), attempts, created_at, published_at. A projection is missing rows and you must decide whether the relay skipped events or the consumer dropped them. Write three queries over the last seven days: one listing every aggregate_id whose published aggregate_version sequence has a hole, one giving per-day counts with a running total, and one returning the newest published event per aggregate. For each, say where the window function is evaluated relative to WHERE and LIMIT. PostgreSQL 16.

Approach

Gaps: compute lead(aggregate_version) OVER (PARTITION BY aggregate_id ORDER BY aggregate_version) in a subquery, then filter next_version <> aggregate_version + 1 in the outer query. Window functions are evaluated after WHERE, GROUP BY and HAVING and before the outer ORDER BY and LIMIT, so the predicate cannot sit in the same WHERE clause and PostgreSQL 16 has no QUALIFY.
Say what the seven-day filter does to the answer: it truncates every partition, so the first row per aggregate has no predecessor inside the window and a hole spanning the boundary is invisible. Widen the window, or join to resource.version as the authority for the true maximum.
Running total: SELECT date_trunc('day', created_at) AS d, count() AS n, sum(count()) OVER (ORDER BY date_trunc('day', created_at) ROWS UNBOUNDED PRECEDING). An aggregate inside a window call is legal because grouping runs before windowing. The grouping key is unique per row here so ROWS and RANGE agree, but write the frame anyway — over ungrouped rows with tied timestamps the default RANGE frame pulls in every peer row and the total jumps.
Newest per aggregate: DISTINCT ON (aggregate_id) ... ORDER BY aggregate_id, aggregate_version DESC is the cheap PostgreSQL-only form when an index matches that order; row_number() OVER (PARTITION BY aggregate_id ORDER BY aggregate_version DESC) = 1 is the portable form and needs a subquery for the same evaluation-order reason as the gap query.

Follow-up

Relay failover redelivers events. Does a duplicate break the gap query, and how would you detect one from this table alone?
Turn the gap check into a continuous monitor rather than a query someone runs after an incident. What does it watch?

Describe the difference between various FPGA/ASIC design methodologies.

Medium · Technical & Domain Knowledge

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

How do you approach Lidar data validation and verification?

Medium · Technical & Domain Knowledge

Approach

Clarify what is being asked and what a complete answer contains.
State your assumptions explicitly before working the problem.
Say what you would check first and why it is the highest-information step.
Work from the requirement backwards to the design.

Follow-up

What assumption would you test first?
How would you know your answer was wrong?

How would you design a system to process real-time data streams from multiple sensors?

Medium · Problem Solving & Algorithms

Approach

Fix the scope first: who calls this, how often, and what they do when it fails.
Name the read and write paths separately; they rarely have the same bottleneck.
Choose a partition key and say what query it makes expensive.
State the consistency you need, and where you are willing to be stale.

Follow-up

What breaks first when traffic grows ten times?
How does this behave when that dependency is down for an hour?

Every query on one table stalls for forty seconds mid-deploy

Medium · lock contention · ddl · migrations

During a release on PostgreSQL, every query touching resource times out for about 40 seconds and then recovers with no intervention. The release ran one migration, ALTER TABLE resource ADD COLUMN archived_reason TEXT, and the migration log shows it completing in 6 ms. Unrelated tables showed no change in error rate. Explain how a 6 ms statement caused a 40-second stall, give the ordered checks you would run on a live system to confirm it, and give the migration procedure that prevents a repeat.

Approach

Separate the statement's duration from the lock's duration. ADD COLUMN with no default is a catalogue-only change and genuinely runs in milliseconds, but it requires ACCESS EXCLUSIVE, and it cannot acquire that until every transaction already touching the table has finished.
Account for the queueing, which is the part that surprises people. A lock request that is waiting blocks later requests for conflicting modes behind it rather than letting them overtake, so one long-open transaction holds the DDL and the DDL holds all the traffic. The stall length is set by the longest open transaction, not by the size of the change.
Confirm on a live system in this order: pg_stat_activity for that table ordered by xact_start, looking for the oldest transaction and specifically for state = idle in transaction; then pg_locks where granted = false to find the waiter; then join them on pid to name blocker and blocked. pg_blocking_pids() does that join for you and is the fastest single call.
Prevent rather than merely time it better. Set lock_timeout to a second or two on the migration session so the DDL abandons the queue after a bounded wait and is retried, instead of holding it for as long as the oldest transaction lives. Be exact about what that buys: queries arriving during the wait still queue behind the pending ACCESS EXCLUSIVE request, so each attempt costs them up to one lock_timeout of added latency. The outage goes from 40 seconds to about one second per attempt, not to zero. Also run migrations away from deploy-time peaks, and put a statement timeout and an idle-in-transaction timeout on the analytics role that opens the long transactions.

Follow-up

The same release also wants NOT NULL on that column. What is the sequence that gets there without a long lock?
Your lock_timeout retry fails ten times in a row because the analytics transaction is always open. What do you change?

Suggested practice checklist

Built from the rounds and topics Aeva candidates report.

Day 1 — Map the Aeva loop

Write out the reported sequence: Recruiter Screen, Hiring Manager Conversation, Technical Assessment.
For each round, write one sentence on what it is judging, from the description above, and mark the one you are least ready for.

Deliverable: A one-page map of the 3 reported rounds, with the weakest marked.

Day 2 — Work Coding Proficiency in C++

Spend the session on Coding Proficiency in C++, which Aeva candidates report being tested on.
Write one worked example in Coding Proficiency in C++ and time yourself on it.

Deliverable: One timed worked example in Coding Proficiency in C++.

Day 3 — Work DSP (Digital Signal Processing)

Spend the session on DSP (Digital Signal Processing), which Aeva candidates report being tested on.
Write one worked example in DSP (Digital Signal Processing) and time yourself on it.

Deliverable: One timed worked example in DSP (Digital Signal Processing).

Day 4 — Work Data Structures & Algorithms (DSA)

Spend the session on Data Structures & Algorithms (DSA), which Aeva candidates report being tested on.
Write one worked example in Data Structures & Algorithms (DSA) and time yourself on it.

Deliverable: One timed worked example in Data Structures & Algorithms (DSA).

Day 5 — Answer out loud: Technical & Domain Knowledge

Answer aloud, timed: Explain your experience with Digital Signal Processing and how you apply it to sensor data.
Answer aloud, timed: How do you optimize C++ code for performance and memory constraints?

Deliverable: Spoken answers to 2 reported Technical & Domain Knowledge question(s), under time.

Day 6 — Answer out loud: Problem Solving & Algorithms

Answer aloud, timed: Walk me through a challenging bug you encountered in a production environment and how you resolved it.
Answer aloud, timed: How would you design a system to process real-time data streams from multiple sensors?

Deliverable: Spoken answers to 2 reported Problem Solving & Algorithms question(s), under time.

Day 7 — Answer out loud: Behavioral & Leadership

Answer aloud, timed: Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.
Answer aloud, timed: How do you handle disagreements with team members regarding technical design choices?

Deliverable: Spoken answers to 2 reported Behavioral & Leadership question(s), under time.

Behavioural preparation

Behavioural rounds judge the decision you made and what it cost.

Explain your experience with Digital Signal Processing and how you apply it to sensor data.

Medium · Technical & Domain Knowledge

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

What are the common challenges in State Estimation and how do you handle noise in sensor data?

Medium · Technical & Domain Knowledge

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Describe a time you had to learn a new technology or domain quickly to solve a project requirement.

Medium · Problem Solving & Algorithms

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Tell me about a time you had to explain a complex technical concept to a non-technical stakeholder.

Medium · Behavioral & Leadership

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

How do you handle disagreements with team members regarding technical design choices?

Medium · Behavioral & Leadership

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

Describe a situation where you had to manage a project under tight deadlines.

Medium · Behavioral & Leadership

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?

What do you do when you are blocked by a dependency on another team?

Medium · Behavioral & Leadership

Approach

Pick a story where you made the decision, not one where you watched it.
State the situation in two sentences and spend the rest on the reasoning.
Give the blast radius: what could have broken, and what you measured.
Name the disagreement and how you resolved it with evidence.

Follow-up

What would you do differently if you ran that again?
How did you know your change caused the improvement?