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View Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at View, you are at the intersection of high-end material science and sophisticated software systems. View is renowned for its intelligent, self-tinting glass, and your role is critical in bridging the gap between hardware performance and the digital user experience. You are responsible for building the robust software foundations that control these complex systems, ensuring that physical environments are optimized for comfort, energy efficiency, and automation. This position demands a unique blend of technical rigor and system-level thinking. Whether you are working on data analysis, firmware integration, or backend infrastructure, your contributions directly impact how buildings function.

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

Focus areas

  • Data Structures
  • Algorithms
  • DOE (Design of Experiments)

The View interview process

View candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Recruiter Screen

Initial screening call with the recruiter to discuss your background and fit for the role.

What to demonstrate

  • Initial screening call with the recruiter to discuss your background and fit for the role
  • Depth in Data Structures

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 Screen

Discussion with the hiring manager to evaluate your technical capabilities and team fit.

What to demonstrate

  • Discussion with the hiring manager to evaluate your technical capabilities and team fit
  • Depth in Data Structures

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 Evaluations

Deep-dive technical assessments to evaluate your problem-solving skills and coding proficiency.

What to demonstrate

  • Deep-dive technical assessments to evaluate your problem-solving skills and coding proficiency
  • Depth in Data Structures

How to prepare

  • Answer aloud and timed: How would you optimize a system to improve heat transfer or energy efficiency?
  • Answer aloud and timed: How do you approach solving a data structure or algorithm problem under time pressure?

Onsite Experience

Intensive, in-person interviews with multiple team members, focusing on technical and behavioral aspects.

What to demonstrate

  • Intensive, in-person interviews with multiple team members
  • Focusing on technical and behavioral aspects

How to prepare

  • Answer aloud and timed: Can you walk me through your logic for a specific coding task?
  • Answer aloud and timed: How do you ensure your code is both efficient and maintainable?

Where candidates lose points

Own your resume

Every line on your resume is fair game. If you list a project, be prepared to explain the technical "why" and "how" behind every decision you made.

Prepare for technical depth

Interviewers at View are often experts in their fields. Do not be surprised if they challenge your assumptions or ask for deeper explanations of your technical choices.

Stay professional under pressure

Some interviewers may be direct or challenging. Maintain your composure, focus on the problem at hand, and keep your communication clear and professional.

Research the product

Understand what the company sells. Knowing the basics of their smart glass technology will help you frame your answers in a way that shows you understand the business context of your work.

Questions & practice

How do you approach solving a data structure or algorithm problem under time pressure?

Medium · Coding & Algorithms

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

Can you walk me through your logic for a specific coding task?

Medium · Coding & Algorithms

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

How do you ensure your code is both efficient and maintainable?

Medium · Coding & Algorithms

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

What testing strategies do you employ to verify your code's reliability?

Medium · Coding & Algorithms

Approach

  1. Restate the input: its shape, its size, and what is guaranteed about it.
  2. Name the brute-force solution and its complexity before improving on it.
  3. Choose the data structure from the access pattern, not from familiarity.
  4. 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?

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

  1. 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.
  2. 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.
  3. 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.
  4. 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?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

  1. One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
  2. Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
  3. State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
  4. Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

  • A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
  • Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

How would you approach a technical challenge involving thin film growth or data analysis?

Medium · Technical Domain & Engineering

Approach

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

Follow-up

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

What is your process for handling complex data sets in a production environment?

Medium · Technical Domain & Engineering

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 optimize a system to improve heat transfer or energy efficiency?

Medium · Technical Domain & Engineering

Approach

  1. Clarify what is being asked and what a complete answer contains.
  2. State your assumptions explicitly before working the problem.
  3. Say what you would check first and why it is the highest-information step.
  4. 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 troubleshooting issues in a system where hardware and software interact?

Medium · Technical Domain & Engineering

Approach

  1. Establish what changed and when, before forming any theory.
  2. Pick a bisection that eliminates candidates whichever way it turns out.
  3. Check the instrumentation before believing the symptom.
  4. Separate the trigger from the cause; the deploy is rarely the bug.

Follow-up

  • What would you look at first, and what would it rule out?
  • How would you tell a cause from a coincidence here?

Suggested practice checklist

Built from the rounds and topics View candidates report.

Day 1 — Map the View loop

  • Write out the reported sequence: Recruiter Screen, Hiring Manager Screen, Technical Evaluations, Onsite Experience.
  • 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 4 reported rounds, with the weakest marked.

Day 2 — Work Data Structures

  • Spend the session on Data Structures, which View candidates report being tested on.
  • Write one worked example in Data Structures and time yourself on it.

Deliverable: One timed worked example in Data Structures.

Day 3 — Work Algorithms

  • Spend the session on Algorithms, which View candidates report being tested on.
  • Write one worked example in Algorithms and time yourself on it.

Deliverable: One timed worked example in Algorithms.

Day 4 — Work DOE (Design of Experiments)

  • Spend the session on DOE (Design of Experiments), which View candidates report being tested on.
  • Write one worked example in DOE (Design of Experiments) and time yourself on it.

Deliverable: One timed worked example in DOE (Design of Experiments).

Day 5 — Answer out loud: Technical Domain & Engineering

  • Answer aloud, timed: How would you approach a technical challenge involving thin film growth or data analysis?
  • Answer aloud, timed: Can you explain your experience with Design of Experiments (DOE) and the use of tools like JMP?

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

Day 6 — Answer out loud: Coding & Algorithms

  • Answer aloud, timed: How do you approach solving a data structure or algorithm problem under time pressure?
  • Answer aloud, timed: Can you walk me through your logic for a specific coding task?

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

Day 7 — Answer out loud: Behavioral & Leadership

  • Answer aloud, timed: Describe a time you had to collaborate with a cross-functional team to solve a difficult problem.
  • Answer aloud, timed: How do you handle situations where you have to defend your technical approach to a senior stakeholder?

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.

Can you explain your experience with Design of Experiments (DOE) and the use of tools like JMP?

Medium · Technical Domain & Engineering

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 collaborate with a cross-functional team to solve a difficult problem.

Medium · Behavioral & Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 situations where you have to defend your technical approach to a senior stakeholder?

Medium · Behavioral & Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 interests you about working for a company that specializes in smart glass technology?

Medium · Behavioral & Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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 learn a new technology or domain quickly to complete a project.

Medium · Behavioral & Leadership

Approach

  1. Pick a story where you made the decision, not one where you watched it.
  2. State the situation in two sentences and spend the rest on the reasoning.
  3. Give the blast radius: what could have broken, and what you measured.
  4. 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?