Interview guides · ASG Platform

ASG Platform Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer at ASG Platform is not merely a coder; you are a builder tasked with architecting the future of an AI-driven ecosystem. This role is designed for high-agency individuals who prefer creating roadmaps over following them. You will be responsible for designing systems that scale before the demand exists, turning ambiguous concepts into robust production systems, and making technical decisions that will define the company’s infrastructure for the next decade. The work is fast-paced, high-impact, and intentionally demanding. You will move away from legacy maintenance and "Jira-ticket factory" environments, instead focusing on core systems that serve large, reputable businesses. Success here requires a blend of deep technical craftsmanship and the ability to solve problems autonomously.

This guide is scoped to a Software Engineer candidate at ASG Platform.

Focus areas

System Design
Scalability
Solutions Architecture

The ASG Platform interview process

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

Screening Call

Initial call to verify your background and technical stack.

What to demonstrate

Initial call to verify your background and technical stack
Depth in System Design

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 Assessment

Challenging assessments involving the development of specific features or applications.

What to demonstrate

Challenging assessments involving the development of specific features or applications
Depth in System Design

How to prepare

Answer aloud and timed: What is your process for debugging a system when documentation or online workarounds are unavailable?
Answer aloud and timed: How do you approach optimizing code performance for a system that must scale rapidly?

Final Review

Evaluation of your performance and alignment with the company's goals.

What to demonstrate

Evaluation of your performance and alignment with the company's goals
Depth in System Design

How to prepare

Answer aloud and timed: Can you explain a complex technical concept you recently learned and how you applied it to a project?
Answer aloud and timed: Describe a time you had to make a technical decision with incomplete information. How did you proceed?

Where candidates lose points

Prioritize the "Why

Don't just show that you can code; explain why you chose a specific architecture or tool.

Be Transparent

If you encounter a problem during an assessment (e.g., an API issue), document your process for trying to fix it. Effort and methodology matter.

Master your Environment

Ensure your local development environment is configured and ready before starting any timed assessment.

Do not attempt to bypass monitoring software or use unauthorized tools during assessments

Integrity is a core value at ASG Platform.

Questions & practice

How do you approach optimizing code performance for a system that must scale rapidly?

Medium · Technical Assessment & Coding

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?

Can you explain a complex technical concept you recently learned and how you applied it to a project?

Medium · Technical Assessment & Coding

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?

Merge partitioned event streams into one ordered feed with bounded lateness

Hard · k-way merge · watermarks · out-of-order streams

The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.

Approach

Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.

Follow-up

The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?

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?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Can you walk me through the architecture of a simple chat application you have built?

Medium · Technical Assessment & Coding

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?

How do you handle API integration errors when a service requires external authentication or payment?

Medium · Technical Assessment & Coding

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?

What is your process for debugging a system when documentation or online workarounds are unavailable?

Medium · Technical Assessment & Coding

Approach

Establish what changed and when, before forming any theory.
Pick a bisection that eliminates candidates whichever way it turns out.
Check the instrumentation before believing the symptom.
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 ASG Platform candidates report.

Day 1 — Map the ASG Platform loop

Write out the reported sequence: Screening Call, Technical Assessment, Final Review.
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 System Design

Spend the session on System Design, which ASG Platform candidates report being tested on.
Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 3 — Work Scalability

Spend the session on Scalability, which ASG Platform candidates report being tested on.
Write one worked example in Scalability and time yourself on it.

Deliverable: One timed worked example in Scalability.

Day 4 — Work Solutions Architecture

Spend the session on Solutions Architecture, which ASG Platform candidates report being tested on.
Write one worked example in Solutions Architecture and time yourself on it.

Deliverable: One timed worked example in Solutions Architecture.

Day 5 — Answer out loud: Technical Assessment & Coding

Answer aloud, timed: Can you walk me through the architecture of a simple chat application you have built?
Answer aloud, timed: How do you handle API integration errors when a service requires external authentication or payment?

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

Day 6 — Answer out loud: Behavioral & Cultural Fit

Answer aloud, timed: Describe a time you had to make a technical decision with incomplete information. How did you proceed?
Answer aloud, timed: Why are you interested in a residency or bootcamp-style environment rather than a traditional corporate role?

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

Day 7 — Dry run for ASG Platform

Run one full mock under time, then write down the two questions you most want to ask your interviewers.

Deliverable: A completed timed mock and two questions to ask.