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Akima Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Akima, you play a vital role in delivering advanced technology solutions that support critical government, defense, and enterprise missions. This position is responsible for designing, developing, and maintaining software applications and systems that solve complex operational challenges. Your work directly impacts how end users interact with high-stakes platforms, ensuring reliability, security, and performance across diverse operational environments. The work at Akima is characterized by its scope and mission-driven focus, spanning specialized domains such as game development, systems engineering, network infrastructure, and process automation. You will frequently collaborate with cross-functional teams, project managers, and defense stakeholders to translate operational requirements into robust software architectures.

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

Focus areas

  • Security Clearance Requirements (Active/SCI/Secret)
  • Software Engineering (General)
  • Network Engineering

The Akima interview process

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

Initial Recruiter Screen

A preliminary discussion to assess your background and fit for the role.

What to demonstrate

  • A preliminary discussion to assess your background and fit for the role
  • Depth in Security Clearance Requirements (Active/SCI/Secret)

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 Deep Dive

In-depth technical interview focusing on your coding skills and problem-solving abilities.

What to demonstrate

  • In-depth technical interview focusing on your coding skills and problem-solving abilities
  • Depth in Security Clearance Requirements (Active/SCI/Secret)

How to prepare

  • Answer aloud and timed: 1–2 sentences introducing the category and what it tests.
  • Answer aloud and timed: Bullet list of realistic example questions: Why are you leaving your current job and what are you looking for in a new position? Can you explain why you changed career paths or why there is a gap in your employment? How would your boss and coworkers describe your working style and management approach? What are your greatest professional achievements and what motivates you daily? Where do you see yourself in five years and what is your dream job?

Behavioral Assessment

Evaluation of your past experiences and behavioral alignment with Akima's values.

What to demonstrate

  • Evaluation of your past experiences and behavioral alignment with Akima's values
  • Depth in Security Clearance Requirements (Active/SCI/Secret)

How to prepare

  • Prepare three examples from your own work, each with a decision you made and an outcome you can quantify.
  • Re-read the description of the behavioral assessment above and write down what you would ask to confirm before it.

Final Offer Discussion

Discussion regarding the job offer and any final questions you may have.

What to demonstrate

  • Discussion regarding the job offer and any final questions you may have
  • Depth in Security Clearance Requirements (Active/SCI/Secret)

How to prepare

  • Work Security Clearance Requirements (Active/SCI/Secret) until you can explain it without notes
  • Work Software Engineering (General) until you can explain it without notes

Where candidates lose points

Align with the mission

Emphasize your dedication to supporting critical operations and client success, as mission alignment is a core cultural pillar at Akima.

Use the STAR method

Structure your behavioral answers by clearly stating the Situation, Task, Action, and Result to keep your responses concise and impactful.

Be clear about your technical stack

When discussing past projects, be ready to explain not just what you built, but why you chose specific tools and architectures.

Ask insightful questions

Prepare thoughtful questions about team structure, project lifecycles, and technical challenges to demonstrate genuine curiosity and engagement.

Address clearances honestly

If the role requires an active security clearance or the ability to obtain one, be transparent about your current clearance status from the very beginning.

Questions & practice

Find overlapping job attempts and peak concurrency from lease records

Medium · sweep line · intervals · leases

A day of job_run history yields about 50,000,000 attempt records: (job_run_id, job_type, attempt, started_at, finished_at which is NULL when the worker died, lease_expires_at). Leases expire on a clock, so a job that outran its lease ran twice. Produce (a) every job_run_id whose attempts overlapped in wall-clock time and (b) the peak number of simultaneously running attempts per job_type with the minute it occurred. Target O(n log n). State how you treat a NULL finished_at and what clock skew does to your answer.

Approach

  1. Define the interval before sorting anything: an attempt occupies [started_at, COALESCE(finished_at, lease_expires_at)). finished_at is observed and lease_expires_at is only a promise, so every attempt without a finish contributes an estimate and the whole result is a lower bound on overlap rather than an exact count.
  2. For peak concurrency, sweep: emit 2n endpoints, sort by (timestamp, kind) with ends ordered before starts at equal timestamps, then walk the sequence maintaining a counter per job_type and record each type's maximum with its timestamp. O(n log n) dominated by the sort, O(n) space, or O(1) extra if the sort is external and the walk streams.
  3. For overlap detection, do not compare attempts pairwise. A single global sort by (job_run_id, started_at) gives both the grouping and the order; within a group, keep the maximum end seen so far and report an overlap exactly when the next start is less than that running maximum, which is one linear pass after the sort.
  4. Half-open intervals matter and are easy to get wrong: with closed intervals an attempt ending at the same millisecond another begins reads as concurrency two, and across 50,000,000 records that artefact swamps the real signal.

Follow-up

  • A handler is not idempotent and you have found 400 overlapping jobs. Which of them actually caused damage, and what would you query to find out?
  • Peak concurrency for one job_type is 4 against a configured cap of 4. Is the cap working, or is the data hiding attempts that never started?

Canonicalise a request body into a stable idempotency fingerprint

Medium · parsing · canonicalisation · hashing

idempotency_key.request_fingerprint is a SHA-256 over the method, path and canonicalised body, and a retry whose fingerprint differs must be rejected with 422 rather than served the stored response. Write the canonicaliser. Bodies are JSON up to 256 KB nested at most 32 levels; clients vary key order, whitespace and unicode escaping, and some send 64-bit ids as JSON numbers. Produce a deterministic byte string such that semantically identical bodies match and any semantic difference does not. State your complexity and name two normalisations you refuse to perform.

Approach

  1. Parse once into a tree, then re-serialise under fixed rules: object keys sorted, array order preserved, one escaping convention, no insignificant whitespace. Parsing is O(n) and sorting keys is O(k log k) per object, so O(n log n) overall with O(depth) stack, and the 32-level cap is enforced during parsing because hostile nesting is how a canonicaliser becomes a stack overflow.
  2. Sort keys by their UTF-8 bytes and say why the obvious implementation is wrong in some runtimes: a default string comparison that orders by UTF-16 code units places surrogate pairs, meaning code points from U+10000 up, below U+E000 to U+FFFF, which is not UTF-8 byte order, so two services written in different languages disagree on the same document.
  3. Do not re-encode numbers through a double. IEEE-754 binary64 represents integers exactly only up to 2^53, so normalising a 19-digit id through a float changes it, and 1 against 1.0 cannot be reconciled without deciding whether they are the same value. Preserve the literal token, and require ids as strings at the API boundary if you want them comparable.
  4. Reject duplicate keys rather than picking one. JSON permits them and parsers disagree, most keeping the last, so any choice you make ties the fingerprint to a parser detail that the code handling the request does not necessarily share.

Follow-up

  • A client sends the same logical request with an extra field your API ignores. Same key, different fingerprint, so you return 422. Is that the right answer?
  • Where does the fingerprint get computed relative to request decompression and the body-size limit?

Identify the heaviest tenants in a five-minute window under memory pressure

Medium · top-k · heavy hitters · streaming

The edge service handles about 3,000 requests per second across roughly 50,000 tenants, peaking near 9,000. Expose the 50 heaviest tenants by request count over the trailing five minutes so limits can be tightened before one tenant's backfill starves the fleet. You may not retain five minutes of raw records. Give the exact solution and its memory, then the bounded-memory approximation with its error stated as a formula, and say which you would ship and at what tenant cardinality that choice changes.

Approach

  1. Do the exact version first, because it is affordable at this cardinality: a ring of 300 one-second counters per tenant, advanced lazily, is 1,200 bytes of counters per tenant and roughly 60 to 90 MB for 50,000 tenants with overhead. Carry a running total and subtract the bucket you overwrite so a window read is O(1) rather than 300 adds.
  2. Extract the top 50 with a size-k min-heap over the tenant sums: O(d log k) for d tenants, against O(d log d) to sort them all. Maintaining the heap continuously instead of on query requires a tenant-to-heap-index map, because incrementing a count already inside the heap means sifting from a known position, and without that map you rebuild the heap on every request.
  3. State the approximation precisely rather than gesturing at sketches. Misra-Gries with m counters retains every item whose true count exceeds N/(m+1), and each retained count underestimates the truth by at most N/(m+1). With m = 1,000 and N = 900,000 requests in the window the error is roughly 900 requests, which is fine for spotting a tenant sending 50,000 and useless for ranking two tenants 200 apart.
  4. Say what breaks when the window slides: Misra-Gries and Space-Saving are insert-only and cannot be decremented as records age out. The workable construction is one summary per sub-window, say ten seconds, with 30 summaries merged at query time, and the merged error is the sum of the per-summary errors, so the bound degrades linearly in the number of sub-windows.

Follow-up

  • The heaviest tenant is heavy because of one export job rather than user traffic. Should the limiter treat those as the same tenant?
  • Two tenants sit tied at the boundary of the top 50. Does your answer flap, and does the flapping matter?

Hold a per-tenant active cap against concurrent creates

Hard · write skew · isolation levels · constraints

A tenant on the standard plan may hold at most 50 resources with status='active'. The create handler runs SELECT count(*) FROM resource WHERE tenant_id = $1 AND status = 'active', compares to 50, then inserts. Two creates arrive 3 ms apart on different instances and the tenant lands at 51. Name the anomaly, say whether PostgreSQL 16 READ COMMITTED or REPEATABLE READ prevents it and why, then give an implementation that holds the cap at READ COMMITTED with the exact statements. Finally, say what changes when the cap is 'at most one running export per tenant' on job_run.

Approach

  1. Name it: write skew. The two transactions read an overlapping set and write disjoint rows, so there is no row-level conflict for the engine to detect and each commit is individually legal.
  2. Rule out the levels precisely. READ COMMITTED takes a fresh snapshot per statement and takes no lock on the counted rows, so both see 49. PostgreSQL's REPEATABLE READ is snapshot isolation: it removes non-repeatable reads and phantoms within the snapshot but still admits write skew, because the anomaly is not a re-read of a changed row, it is a read of a set that a concurrent transaction invalidates. Only SERIALIZABLE closes it, by tracking the read dependency and aborting one transaction with SQLSTATE 40001 — a guarantee that exists only if the application re-runs the whole transaction from the read.
  3. Convert the set predicate into a single-row conflict: keep tenant.active_resource_count and run UPDATE tenant SET active_resource_count = active_resource_count + 1 WHERE tenant_id = $1 AND active_resource_count < 50 in the same transaction as the INSERT. Zero affected rows is the cap, returned as 409. The row lock serialises the decision at any isolation level, and contention is bounded to one tenant's row — which is also the fair-scheduling unit, unlike a global counter that would convoy every tenant behind one row.
  4. State the cost you just took on: a counter is a second source of truth that can drift, so every path that changes status must adjust it inside the same transaction, and a periodic reconciliation has to exist, with resource_revision as the authority for what the count should have been.

Follow-up

  • A resource moves from archived back to active. Which statements change, and what breaks if the counter update and the status change land in different transactions?
  • The cap becomes plan-dependent and a plan can change mid-month. Where does the number 50 live, and who reads it?

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?

1–2 sentences introducing the category and what it tests.

Medium · Career and Professional Background

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?

Bullet list of realistic example questions: Why are you leaving your current job and what are you looking for

Medium · Career and Professional Background

Bullet list of realistic example questions: Why are you leaving your current job and what are you looking for in a new position? Can you explain why you changed career paths or why there is a gap in your employment? How would your boss and coworkers describe your working style and management approach? What are your greatest professional achievements and what motivates you daily? Where do you see yourself in five years and what is your dream job?

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?

1–2 sentences introducing the category and what it tests.

Medium · Working Style and Problem-Solving

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?

Bullet list of realistic example questions: How do you prioritize your work and deal with pressure or stressfu

Medium · Working Style and Problem-Solving

Bullet list of realistic example questions: How do you prioritize your work and deal with pressure or stressful situations? What type of work environment do you prefer and how do you like to be managed? What do you think we could do better or differently as an organization? How many tennis balls can you fit into a limousine? Sell me this pen.

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?

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

  1. 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.
  2. 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.
  3. 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.
  4. 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 Akima candidates report.

Day 1 — Map the Akima loop

  • Write out the reported sequence: Initial Recruiter Screen, Technical Deep Dive, Behavioral Assessment, Final Offer Discussion.
  • 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 Security Clearance Requirements (Active/SCI/Secret)

  • Spend the session on Security Clearance Requirements (Active/SCI/Secret), which Akima candidates report being tested on.
  • Write one worked example in Security Clearance Requirements (Active/SCI/Secret) and time yourself on it.

Deliverable: One timed worked example in Security Clearance Requirements (Active/SCI/Secret).

Day 3 — Work Software Engineering (General)

  • Spend the session on Software Engineering (General), which Akima candidates report being tested on.
  • Write one worked example in Software Engineering (General) and time yourself on it.

Deliverable: One timed worked example in Software Engineering (General).

Day 4 — Work Network Engineering

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

Deliverable: One timed worked example in Network Engineering.

Day 5 — Answer out loud: Behavioral and Culture Fit

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests.
  • Answer aloud, timed: Bullet list of realistic example questions: Why do you want to work at Akima? Why do you want this job and why should we hire you? Tell me about a challenge or conflict you’ve faced at work, and how you dealt with it. Tell me about a time you demonstrated leadership skills or disagreed with a decision. Tell me about a time you made a mistake or experienced failure, and what you learned.

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

Day 6 — Answer out loud: Career and Professional Background

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests.
  • Answer aloud, timed: Bullet list of realistic example questions: Why are you leaving your current job and what are you looking for in a new position? Can you explain why you changed career paths or why there is a gap in your employment? How would your boss and coworkers describe your working style and management approach? What are your greatest professional achievements and what motivates you daily? Where do you see yourself in five years and what is your dream job?

Deliverable: Spoken answers to 2 reported Career and Professional Background question(s), under time.

Day 7 — Answer out loud: Working Style and Problem-Solving

  • Answer aloud, timed: 1–2 sentences introducing the category and what it tests.
  • Answer aloud, timed: Bullet list of realistic example questions: How do you prioritize your work and deal with pressure or stressful situations? What type of work environment do you prefer and how do you like to be managed? What do you think we could do better or differently as an organization? How many tennis balls can you fit into a limousine? Sell me this pen.

Deliverable: Spoken answers to 2 reported Working Style and Problem-Solving question(s), under time.

Behavioural preparation

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

1–2 sentences introducing the category and what it tests.

Medium · Behavioral and Culture Fit

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?

Bullet list of realistic example questions: Why do you want to work at Akima? Why do you want this job and why

Medium · Behavioral and Culture Fit

Bullet list of realistic example questions: Why do you want to work at Akima? Why do you want this job and why should we hire you? Tell me about a challenge or conflict you’ve faced at work, and how you dealt with it. Tell me about a time you demonstrated leadership skills or disagreed with a decision. Tell me about a time you made a mistake or experienced failure, and what you learned.

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?

Argue against a design, lose, and commit anyway

Medium · disagreement · service boundaries · decision records

Describe a design you argued against and lost. State the failure you predicted as a named mechanism, not a feeling about complexity: two services that would need one transaction, a projection with no rebuild path, a write path with no idempotency key. Say what evidence you brought, what the decision maker weighed instead, and what you did after the decision was made: what you instrumented, what you wrote down, and whether the prediction came true. Five minutes.

Approach

  1. State the prediction in falsifiable form up front: the mechanism, the condition that triggers it, and the observable outcome. A prediction that cannot be checked also cannot be credited to you later.
  2. Show the evidence you had at the time and label each piece honestly as measured, analogous, or intuition. Keeping the intuition is fine; disguising it as data is the thing that erodes your standing in the next argument.
  3. Represent the opposing case at full strength, including the constraint you did not control: a fixed date, a team boundary, or the fact that the decision was cheap to reverse and yours was not.
  4. Make disagree-and-commit concrete. Name the artefact you left behind so the prediction could be settled without you: the alert and its threshold, the counter on the dashboard, the decision note that recorded the trade-off and the condition that would revisit it.

Follow-up

  • What threshold on that alert would have proved you right, and did anyone ever look at it?
  • If the same proposal arrived tomorrow with the same deadline, would you argue it the same way?