A Software Engineer at Kharon is a foundational architect of the digital infrastructure that connects global trade leaders to critical risk intelligence. You are not just writing code; you are building the high-performance engines that make complex global security data discoverable, accessible, and actionable. Your work directly impacts how financial institutions and multinational corporations navigate sanctions, export controls, and emerging global threats. This role sits at the intersection of high-traffic content delivery and secure, data-driven SaaS functionality. You will be responsible for the "Growth & Web Experience" layer, ensuring that Kharon’s marketing presence is as technically sophisticated as its intelligence products. Whether you are optimizing Core Web Vitals for search dominance, scaling headless CMS integrations, or architecting secure, frictionless login walls, your contributions are the bridge between the company's research and the global marketplace.
Technical Screens
reportedInitial evaluations of your technical expertise through coding challenges or assessments.
What to demonstrate
- Initial evaluations of your technical expertise through coding challenges or assessments
- Depth in React
How to prepare
- Answer aloud and timed: How do you decide between Static Site Generation (SSG) and Server-Side Rendering (SSR) for a high-traffic marketing site?
- Answer aloud and timed: How would you approach improving Core Web Vitals for a content-heavy page?
Architectural Discussions
reportedIn-depth conversations about system design and architectural principles relevant to the role.
What to demonstrate
- In-depth conversations about system design and architectural principles relevant to the role
- Depth in React
How to prepare
- Answer aloud and timed: Explain your strategy for implementing structured data (JSON-LD) to ensure rich snippets in search results.
- Answer aloud and timed: How do you manage global state and authentication flows in a Next.js application?
Behavioral Interviews
reportedInterviews focusing on your alignment with the company's mission-driven culture and past experiences.
What to demonstrate
- Interviews focusing on your alignment with the company's mission-driven culture and past experiences
- Depth in React
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 interviews above and write down what you would ask to confirm before it.
PracHub editorial advice for the preparation topics above.
Own your narrative
When discussing past projects, be ready to explain the trade-offs you made. Why did you choose that specific library? What would you do differently today?
Think like a user
At Kharon, we are obsessed with the user journey. Always frame your technical solutions in terms of how they improve the discoverability or accessibility of our intelligence.
Be prepared for ambiguity
We often work on complex, evolving problems. Show us how you gather requirements and iterate toward a solution.
Prepare your questions
We view the interview as a two-way conversation. Ask about our roadmap, our design system, or how we balance speed with security.
Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.
Explain your strategy for implementing structured data (JSON-LD) to ensure rich snippets in search results.
Explain your strategy for implementing structured data (JSON-LD) to ensure rich snippets in search results.
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?
Find overlapping job attempts and peak concurrency from lease records
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
- 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.
- 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.
- 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.
- 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?
Identify the heaviest tenants in a five-minute window under memory pressure
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
- 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.
- 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.
- 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.
- 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?
Explain why the owner filter ignores the listing index
The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.
Approach
- Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
- For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
- Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
- Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.
Follow-up
- 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
- A dashboard runs this for 40 owners in one page load. What changes about the design?
Denormalise tenant onto revisions and backfill it live
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?
How do you decide between Static Site Generation (SSG) and Server-Side Rendering (SSR) for a high-traffic mark
How do you decide between Static Site Generation (SSG) and Server-Side Rendering (SSR) for a high-traffic marketing site?
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 would you approach improving Core Web Vitals for a content-heavy page?
How would you approach improving Core Web Vitals for a content-heavy page?
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 manage global state and authentication flows in a Next.js application?
How do you manage global state and authentication flows in a Next.js application?
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?
Describe a time you had to integrate a complex third-party API or marketing tool into a React application.
Describe a time you had to integrate a complex third-party API or marketing tool into a React application.
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 approach to debugging performance bottlenecks that span the frontend and the backend?
What is your approach to debugging performance bottlenecks that span the frontend and the backend?
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?
Built from the rounds and topics Kharon candidates report.
Prepare, practise & reflect
One practical outcome each day. Spend longer where you need it.
0 / 7 done01Map the Kharon loop
- Write out the reported sequence: Technical Screens, Architectural Discussions, Behavioral 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.
02Work React
- Spend the session on React, which Kharon candidates report being tested on.
- Write one worked example in React and time yourself on it.
Deliverable: One timed worked example in React.
03Work Next.js
- Spend the session on Next.js, which Kharon candidates report being tested on.
- Write one worked example in Next.js and time yourself on it.
Deliverable: One timed worked example in Next.js.
04Work Technical SEO
- Spend the session on Technical SEO, which Kharon candidates report being tested on.
- Write one worked example in Technical SEO and time yourself on it.
Deliverable: One timed worked example in Technical SEO.
05Answer out loud: Frontend Architecture & Performance
- Answer aloud, timed: How do you decide between Static Site Generation (SSG) and Server-Side Rendering (SSR) for a high-traffic marketing site?
- Answer aloud, timed: How would you approach improving Core Web Vitals for a content-heavy page?
Deliverable: Spoken answers to 2 reported Frontend Architecture & Performance question(s), under time.
06Answer out loud: Full-Stack & Integration
- Answer aloud, timed: Describe a time you had to integrate a complex third-party API or marketing tool into a React application.
- Answer aloud, timed: How do you handle authentication and session management across different subdomains or gated content areas?
Deliverable: Spoken answers to 2 reported Full-Stack & Integration question(s), under time.
07Answer out loud: Behavioral & Collaborative Problem Solving
- Answer aloud, timed: Tell me about a time you had to explain a complex technical decision to a stakeholder from a marketing or design team.
- Answer aloud, timed: How do you balance "pixel-perfect" design requirements with the need for rapid deployment and site performance?
Deliverable: Spoken answers to 2 reported Behavioral & Collaborative Problem Solving question(s), under time.
Expand any day for tasks and deliverables. Your progress is saved on this device.
Behavioural rounds judge the decision you made and what it cost.
How do you handle authentication and session management across different subdomains or gated content areas?
How do you handle authentication and session management across different subdomains or gated content areas?
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 decision to a stakeholder from a marketing or desi
Tell me about a time you had to explain a complex technical decision to a stakeholder from a marketing or design team.
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 balance "pixel-perfect" design requirements with the need for rapid deployment and site performance
How do you balance "pixel-perfect" design requirements with the need for rapid deployment and site performance?
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 project where you had to lead a technical initiative from design to implementation.
Describe a project where you had to lead a technical initiative from design to implementation.
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?
- 01
How do you handle authentication and session management across different subdomains or gated content areas?
- 02
Tell me about a time you had to explain a complex technical decision to a stakeholder from a marketing or design team.
- 03
How do you balance "pixel-perfect" design requirements with the need for rapid deployment and site performance?
- 04
Describe a project where you had to lead a technical initiative from design to implementation.
How much time should I dedicate to preparing for the technical portion?
Dedicate enough time to be comfortable articulating your past architectural decisions. We focus more on your reasoning than on rote memorization of syntax.
Kharon Software Engineer candidate reports ↗Is this role fully remote?
No, this position requires in-office attendance at our Denver, CO location at least 3 days a week.
Kharon Software Engineer candidate reports ↗What defines a "successful" candidate at Kharon?
Successful candidates are those who balance technical rigor with a deep empathy for the user experience. You must be able to hold your own in architectural reviews while remaining a collaborative partner to our marketing and design teams.
Kharon Software Engineer candidate reports ↗How does the interview process vary for this role?
Because of the "Growth & Web Experience" focus, expect a heavier emphasis on SEO and frontend performance compared to core platform engineering roles.
Kharon Software Engineer candidate reports ↗What topics does Kharon test in interviews?
Kharon interviews most often cover Research methodology, Problem Solving, Kubernetes, Agentic AI Engineering, and React. The exact emphasis depends on the specific role you apply for.
Kharon Software Engineer candidate reports ↗Sources & methodology 3 sources ↗
No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.
- 01Kharon Software Engineer candidate reports ↗
Company-reported rounds, questions and FAQ.
Candidate reports · Accessed 2026-09-22 - 02PracHub Software Engineer practice ↗
PracHub practice material, not company-reported.
PracHub page · Accessed 2026-09-22 - 03PracHub preparation framework ↗
PracHub preparation guidance.
PracHub page · Accessed 2026-09-22
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