Interview guides · Semgrep

Semgrep Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at Semgrep plays a pivotal role in advancing the company's core mission: making it expensive to exploit software. At its heart, Semgrep is a developer-first application security platform designed to deliver industry-leading code, dependency, and secrets scanning. Unlike traditional security tools that slow down development cycles, Semgrep is built to seamlessly integrate into the developer workflow, catching vulnerabilities early and helping teams fix them faster. In this role, you will contribute directly to products that analyze codebases at massive scale. This involves solving complex problems around static analysis, parsing, program analysis, and software composition analysis (SCA).

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

Focus areas

Software Composition Analysis (SCA)
Software Engineering Leadership
Supply Chain Security

The Semgrep interview process

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

Recruiter Phone Screen

Initial call to discuss your background, motivation for joining Semgrep, and career goals.

What to demonstrate

Initial call to discuss your background, motivation for joining Semgrep, and career goals
Depth in Software Composition Analysis (SCA)

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.

Technical Screening

Includes a practical coding challenge or a custom programming exercise.

What to demonstrate

Includes a practical coding challenge or a custom programming exercise
Depth in Software Composition Analysis (SCA)

How to prepare

Answer aloud and timed: Design and write a custom parser or utility in Python to process and validate structured configuration files.
Answer aloud and timed: Implement a rate-limiter or a basic caching mechanism to optimize network calls.

Remote Onsite Interviews

Series of interviews covering system design, project planning, code reviews, and behavioral discussions.

What to demonstrate

Series of interviews covering system design, project planning, code reviews, and behavioral discussions
Depth in Software Composition Analysis (SCA)

How to prepare

Answer aloud and timed: Walk through a design discussion for a developer-facing tool, outlining API structures, database schemas, and integration points.
Answer aloud and timed: How would you plan and break down the development of a new feature for a static analysis platform into iterative, shippable milestones?

Where candidates lose points

Focus on working code

During coding rounds, prioritize getting a functional solution working before optimizing. The interviewers value working software and practical problem-solving over premature optimization.

Semgrep values practical engineering

Focus your preparation on writing clean, functional code that handles real-world scenarios rather than memorizing complex algorithmic puzzles.

Communicate your thought process

Treat the interview as a collaborative pairing session. Talk through your design decisions, explain your trade-offs, and ask clarifying questions early.

Show empathy for the developer

Remember that Semgrep builds tools for developers. Whenever you design an API, write code, or discuss a feature, keep the end-user developer's experience in mind.

Questions & practice

Write a program that models a state machine, such as a vending machine, managing state transitions, inputs, an

Medium · Practical Coding & Implementation

Write a program that models a state machine, such as a vending machine, managing state transitions, inputs, and error conditions.

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?

Implement a rate-limiter or a basic caching mechanism to optimize network calls.

Medium · Practical Coding & Implementation

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?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

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?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
How do you honour an erasure request while resource_revision.actor_user_id still references this table?

Implement a script or service that makes HTTP requests to an external API, parses the JSON payload, and filter

Medium · Practical Coding & Implementation

Implement a script or service that makes HTTP requests to an external API, parses the JSON payload, and filters the results based on specific business logic.

Approach

Say who the caller is and what they do when the call fails halfway.
Define the identity of a request so a retry cannot double-apply it.
Separate accepted, pending, failed and confirmed; they are different facts.
Design the error taxonomy before the success shape; callers branch on it.

Follow-up

What happens if the caller retries after a timeout?
How does a client discover it is on an old version of this contract?

Design and write a custom parser or utility in Python to process and validate structured configuration files.

Medium · Practical Coding & Implementation

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?

Walk through a design discussion for a developer-facing tool, outlining API structures, database schemas, and

Medium · System Design & Project Planning

Walk through a design discussion for a developer-facing tool, outlining API structures, database schemas, and integration points.

Approach

Say who the caller is and what they do when the call fails halfway.
Define the identity of a request so a retry cannot double-apply it.
Separate accepted, pending, failed and confirmed; they are different facts.
Design the error taxonomy before the success shape; callers branch on it.

Follow-up

What happens if the caller retries after a timeout?
How does a client discover it is on an old version of this contract?

How would you plan and break down the development of a new feature for a static analysis platform into iterati

Medium · System Design & Project Planning

How would you plan and break down the development of a new feature for a static analysis platform into iterative, shippable milestones?

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?

Design a scalable pipeline to ingest, process, and store dependency vulnerability data from multiple external

Medium · System Design & Project Planning

Design a scalable pipeline to ingest, process, and store dependency vulnerability data from multiple external feeds.

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?

Discuss how you would balance addressing technical debt with delivering new user-facing features on a tight sc

Medium · System Design & Project Planning

Discuss how you would balance addressing technical debt with delivering new user-facing features on a tight schedule.

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?

Read latency spikes on a sixty-second sawtooth

Medium · cache stampede · single-flight · ttl

The cached listing read path serves about 14k reads/second at an 85% hit rate. p99 sits at 35 ms for 57 seconds, jumps to 900 ms for 3, and repeats. During each spike the primary shows several hundred identical listing queries starting within the same millisecond, all carrying one large tenant's id. Cache entries use a 60-second TTL. Give the mechanism, the ordered checks, the fix, and the correctness hazard your fix must not introduce.

Approach

Match the period to a configured number before theorising about load. A spike every 60 seconds against a 60-second TTL is an entry expiring, and you confirm it by correlating spike timestamps with the entry's write time rather than with the traffic curve. If the period had matched a cron or a GC interval instead, this is a different investigation.
Establish the concurrency of the miss. Several hundred identical queries in one millisecond means the miss path has no coalescing: every request that arrives between expiry and repopulation recomputes. The herd size is that key's arrival rate times its recompute time, so at 1.2k reads/second for the hot key and a 250 ms recompute you expect about 300 concurrent misses, which matches what is observed.
Add single-flight on the miss path so one caller per key recomputes under a short-lived lock while the rest wait for its result. Prefer stale-while-revalidate where the read tolerates it: return the expired value immediately and refresh asynchronously, which removes the latency spike rather than serialising it into a queue of waiters.
De-synchronise the keys. Write TTLs with jitter, for example 60 seconds plus or minus 10%, so a deploy or a mass invalidation does not align every key on the same second and turn a per-key herd into a fleet-wide one.

Follow-up

The same sawtooth appears on a key that is invalidated on write rather than expired. Is that the same bug?
How does your answer change if the recompute takes 4 seconds instead of 250 ms?

Suggested practice checklist

Built from the rounds and topics Semgrep candidates report.

Day 1 — Map the Semgrep loop

Write out the reported sequence: Recruiter Phone Screen, Technical Screening, Remote Onsite Interviews.
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 Software Composition Analysis (SCA)

Spend the session on Software Composition Analysis (SCA), which Semgrep candidates report being tested on.
Write one worked example in Software Composition Analysis (SCA) and time yourself on it.

Deliverable: One timed worked example in Software Composition Analysis (SCA).

Day 3 — Work Software Engineering Leadership

Spend the session on Software Engineering Leadership, which Semgrep candidates report being tested on.
Write one worked example in Software Engineering Leadership and time yourself on it.

Deliverable: One timed worked example in Software Engineering Leadership.

Day 4 — Work Supply Chain Security

Spend the session on Supply Chain Security, which Semgrep candidates report being tested on.
Write one worked example in Supply Chain Security and time yourself on it.

Deliverable: One timed worked example in Supply Chain Security.

Day 5 — Answer out loud: Practical Coding & Implementation

Answer aloud, timed: Write a program that models a state machine, such as a vending machine, managing state transitions, inputs, and error conditions.
Answer aloud, timed: Implement a script or service that makes HTTP requests to an external API, parses the JSON payload, and filters the results based on specific business logic.

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

Day 6 — Answer out loud: System Design & Project Planning

Answer aloud, timed: Walk through a design discussion for a developer-facing tool, outlining API structures, database schemas, and integration points.
Answer aloud, timed: How would you plan and break down the development of a new feature for a static analysis platform into iterative, shippable milestones?

Deliverable: Spoken answers to 2 reported System Design & Project Planning question(s), under time.

Day 7 — Answer out loud: Behavioral & Cultural Alignment

Answer aloud, timed: Why do you want to work at Semgrep, and what excites you about developer tooling and application security?
Answer aloud, timed: Describe a time when you had to deliver constructive feedback during a code review. How did you handle it, and what was the outcome?

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

Behavioural preparation

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

Why do you want to work at Semgrep, and what excites you about developer tooling and application security?

Medium · Behavioral & Cultural Alignment

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 when you had to deliver constructive feedback during a code review. How did you handle it, and

Medium · Behavioral & Cultural Alignment

Describe a time when you had to deliver constructive feedback during a code review. How did you handle it, and what was the outcome?

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?

Talk about a project where you had to make a technical compromise to meet a deadline. How did you decide what

Medium · Behavioral & Cultural Alignment

Talk about a project where you had to make a technical compromise to meet a deadline. How did you decide what to sacrifice?

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 ambiguous requirements when starting a new technical initiative?

Medium · Behavioral & Cultural Alignment

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?