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Selby Jennings Software Engineer Interview Guide

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

The 60-second brief

A Software Engineer placed through Selby Jennings occupies a highly critical role at the intersection of technology and elite financial markets. Selby Jennings is a premier global recruitment firm that partners with the world's leading hedge funds, proprietary trading shops, market makers, and investment banks. In this role, you are not just writing standard application code; you are building the high-performance, low-latency infrastructure that powers global financial systems, prediction markets, and algorithmic trading platforms. The impact of your work is immediate and highly visible. You will design and optimize systems where microseconds directly translate to millions of dollars in revenue.

This guide is scoped to a Software Engineer candidate at Selby Jennings.

Focus areas

  • Python
  • Software Engineering
  • Algorithmic Trading

The Selby Jennings interview process

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

Recruiter Call

Initial contact with a recruiter to assess your technical background, career goals, and salary expectations.

What to demonstrate

  • Initial contact with a recruiter to assess your technical background, career goals, and salary expectations
  • Depth in Python

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 Evaluation

Online coding challenge or technical phone screen focusing on algorithms, data structures, and system design.

What to demonstrate

  • Online coding challenge or technical phone screen focusing on algorithms, data structures, and system design
  • Depth in Python

How to prepare

  • Answer aloud and timed: Optimize a memory-intensive Python script to process large datasets of historical trading ticks.
  • Answer aloud and timed: Implement an efficient sorting algorithm for a highly constrained, low-latency environment.

Client Interviews

Series of deep-dive technical interviews with the end client to evaluate domain-specific knowledge and cultural fit.

What to demonstrate

  • Series of deep-dive technical interviews with the end client to evaluate domain-specific knowledge and cultural fit
  • Depth in Python

How to prepare

  • Answer aloud and timed: How would you detect and resolve deadlocks in a multi-threaded execution engine?
  • Answer aloud and timed: Design a distributed prediction market platform capable of handling millions of concurrent order submissions.

Onsite/Virtual Loop

Comprehensive onsite or virtual interviews that test your skills and fit for the role.

What to demonstrate

  • Comprehensive onsite or virtual interviews that test your skills and fit for the role
  • Depth in Python

How to prepare

  • Answer aloud and timed: How would you architect a real-time market data feed handler that guarantees zero message loss?
  • Answer aloud and timed: Describe how you would minimize network latency and garbage collection overhead in a Java-based trading system.

Where candidates lose points

Own your tech stack preferences

Do not let external pressure push you into roles or technology stacks that do not align with your career goals. Be clear about what you want to build.

Over-communicate during system design

Walk your interviewer through your thought process, explicitly stating the trade-offs between latency, complexity, and reliability.

Prepare for live coding

Practice coding on a whiteboard or in a simple text editor without the aid of IDE auto-completion, as many client technical screens use basic coding environments.

Client interview processes in quantitative finance are notoriously fast-paced but can have variable feedback loops

Proactively follow up with your recruiter if you do not hear back within 48 hours of submitting a coding challenge.

Questions & practice

Implement a lock-free queue in C++ and explain how you prevent race conditions.

Medium · Coding and Algorithmic Problem Solving

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Optimize a memory-intensive Python script to process large datasets of historical trading ticks.

Medium · Coding and Algorithmic Problem Solving

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

Implement an efficient sorting algorithm for a highly constrained, low-latency environment.

Medium · Coding and Algorithmic Problem Solving

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?

Describe how you would minimize network latency and garbage collection overhead in a Java-based trading system

Medium · System Design and Architecture

Describe how you would minimize network latency and garbage collection overhead in a Java-based trading system.

Approach

  1. Say what the runtime actually does before reasoning about the code.
  2. Name what is shared across threads and what owns each piece of state.
  3. Identify the window where an invariant is briefly untrue.
  4. Distinguish a value from a reference to it, and say which one you handed out.

Follow-up

  • What happens if two callers reach this at the same time?
  • Where could this allocate more than you expect?

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?

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?

Given a stream of financial market data, design an algorithm to find the moving average within a sliding time

Medium · Coding and Algorithmic Problem Solving

Given a stream of financial market data, design an algorithm to find the moving average within a sliding time window.

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 distributed prediction market platform capable of handling millions of concurrent order submissions.

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 architect a real-time market data feed handler that guarantees zero message loss?

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 fault-tolerant configuration management service for a fleet of trading engines.

Medium · System Design and Architecture

Approach

  1. Fix the scope first: who calls this, how often, and what they do when it fails.
  2. Name the read and write paths separately; they rarely have the same bottleneck.
  3. Choose a partition key and say what query it makes expensive.
  4. 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 detect and resolve deadlocks in a multi-threaded execution engine?

Medium · Coding and Algorithmic Problem Solving

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?

Share an experience where you had to debug a critical production issue under extreme time constraints.

Medium · Behavioral and Professional Alignment

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 Selby Jennings candidates report.

Day 1 — Map the Selby Jennings loop

  • Write out the reported sequence: Recruiter Call, Technical Evaluation, Client Interviews, Onsite/Virtual Loop.
  • 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 Python

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

Deliverable: One timed worked example in Python.

Day 3 — Work Software Engineering

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

Deliverable: One timed worked example in Software Engineering.

Day 4 — Work Algorithmic Trading

  • Spend the session on Algorithmic Trading, which Selby Jennings candidates report being tested on.
  • Write one worked example in Algorithmic Trading and time yourself on it.

Deliverable: One timed worked example in Algorithmic Trading.

Day 5 — Answer out loud: Coding and Algorithmic Problem Solving

  • Answer aloud, timed: Implement a lock-free queue in C++ and explain how you prevent race conditions.
  • Answer aloud, timed: Given a stream of financial market data, design an algorithm to find the moving average within a sliding time window.

Deliverable: Spoken answers to 2 reported Coding and Algorithmic Problem Solving question(s), under time.

Day 6 — Answer out loud: System Design and Architecture

  • Answer aloud, timed: Design a distributed prediction market platform capable of handling millions of concurrent order submissions.
  • Answer aloud, timed: How would you architect a real-time market data feed handler that guarantees zero message loss?

Deliverable: Spoken answers to 2 reported System Design and Architecture question(s), under time.

Day 7 — Answer out loud: Behavioral and Professional Alignment

  • Answer aloud, timed: Describe a time when you disagreed with a team member regarding a technical implementation. How did you resolve it?
  • Answer aloud, timed: How do you handle situations where a recruiter or stakeholder pushes you toward a technology stack you do not believe is the right fit?

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

Behavioural preparation

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

How do you handle database replication and consistency across geographically distributed trading hubs?

Medium · System Design and Architecture

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 when you disagreed with a team member regarding a technical implementation. How did you resolv

Medium · Behavioral and Professional Alignment

Describe a time when you disagreed with a team member regarding a technical implementation. How did you resolve it?

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 a recruiter or stakeholder pushes you toward a technology stack you do not

Medium · Behavioral and Professional Alignment

How do you handle situations where a recruiter or stakeholder pushes you toward a technology stack you do not believe is the right 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?

How do you manage your workload and maintain communication when faced with long, multi-stage interview loops?

Medium · Behavioral and Professional Alignment

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?