Morgan Lewis Software Engineer Interview Guide

The 60-second brief

The role of a Software Engineer at Morgan Lewis is pivotal in driving technological innovation and improving the efficiency of legal services. In this position, you will be integral to developing and maintaining software solutions that support the firm’s legal operations, enhancing the way teams collaborate and serve clients. The complexity and scale of projects you will work on ensure that your contributions directly impact both users and business outcomes, fostering a dynamic environment where your technical skills can shine. As a Software Engineer, you will engage with a variety of products and technologies that facilitate legal processes, such as document management systems, case management applications, and client-facing platforms. The role demands not only technical prowess but also a strategic mindset to navigate the unique challenges faced by the legal industry.

This guide is scoped to a Software Engineer candidate at Morgan Lewis.

Focus areas

• SQL
• Problem Solving
• C#

The Morgan Lewis interview process

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

HR Screening

Initial screening conducted by HR to assess basic qualifications and fit.

What to demonstrate

• Initial screening conducted by HR to assess basic qualifications and fit
• Depth in SQL

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 Interviews

Multiple technical interviews focusing on coding challenges and technical skills.

What to demonstrate

• Multiple technical interviews focusing on coding challenges and technical skills
• Depth in SQL

How to prepare

• Answer aloud and timed: Describe your experience with SQL, particularly with JOIN operations and the BETWEEN clause.
• Answer aloud and timed: What is the role of indexing in a database?

Cultural Fit Assessment

Discussions to evaluate how well you align with the firm's values and collaborative approach.

What to demonstrate

• Discussions to evaluate how well you align with the firm's values and collaborative approach
• Depth in SQL

How to prepare

• Answer aloud and timed: How would you design a scalable system for managing legal documents?
• Answer aloud and timed: What are the key considerations when designing a microservices architecture?

Where candidates lose points

Practice Coding

Regularly engage with coding problems to sharpen your skills and build confidence before the interview.

Understand the Legal Landscape

Familiarize yourself with how technology intersects with legal processes, as this knowledge will enhance your discussions during interviews.

Showcase Teamwork

Be prepared to share examples that highlight your collaborative spirit and ability to work effectively in teams.

Communicate Clearly

Practice articulating your thought process during problem-solving to demonstrate your communication skills clearly.

Questions & practice

How do you find the maximum difference between repeated elements in an array?

Medium · Technical Questions

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?

Write a function to check if a string is a palindrome.

Medium · Coding Challenges

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?

Solve a coding problem that involves data structures such as arrays or linked lists.

Medium · Coding Challenges

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 your experience with SQL, particularly with JOIN operations and the BETWEEN clause.

Medium · Technical Questions

Approach

1. Name the grain you start from and join outward from it.
2. Check whether any join is one-to-many before aggregating, or the sums inflate.
3. Say which index the query would use, and what makes it unusable.
4. Handle the rows that do not match: that is usually the actual question.

Follow-up

• How does the query change if that join becomes one-to-many?
• What happens to this when the table is ten times larger?

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?

Explain the difference between TCP and UDP protocols.

Medium · Technical Questions

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?

What is the role of indexing in a database?

Medium · Technical Questions

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?

How would you design a scalable system for managing legal documents?

Medium · System Design & 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?

What are the key considerations when designing a microservices architecture?

Medium · System Design & 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?

Given a specific software challenge, outline how you would approach solving it step-by-step.

Medium · Problem-Solving Questions

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?

p99 jumped on one listing filter while p50 stayed flat

Medium · query planning · composite index · percentiles

After a release that added an owner_user_id filter to the resource listing, p99 rose from 90 ms to 1.9 s while p50 stayed at 40 ms. Traffic and row counts are unchanged. resource carries the index (tenant_id, status, updated_at DESC, resource_id DESC). The new query filters tenant_id and owner_user_id, orders by updated_at DESC, resource_id DESC, and takes 20 rows. On PostgreSQL, explain the shape of the regression, prove it from a query plan, and give the index you would add.

Approach

1. Start from the shape. A flat p50 with a moved p99 means a subset of requests changed cost, not all of them, so the first job is naming the subset. Bucket the endpoint's latency by the tenant's row count; the natural hypothesis is that large tenants are a small share of requests and all of the tail.
2. Get the plan for the new query on a large tenant with EXPLAIN (ANALYZE, BUFFERS). Expect an index scan over the tenant's range, a filter discarding most of it, then a Sort feeding the Limit, possibly reporting Sort Method: external merge Disk. Read actual rows on the scan node, not estimated.
3. Explain why the existing index cannot serve it. A composite B-tree is seekable only as a left prefix, and with no equality predicate on status the scan cannot treat updated_at as an ordering, because rows in the tenant's range are ordered by status first. Everything matching must be read and sorted before LIMIT 20 can apply, so a tenant with 400,000 rows pays 400,000 rows to return 20.
4. Add (tenant_id, owner_user_id, updated_at DESC, resource_id DESC). Equality on the first two columns leaves the index ordered by updated_at within that pair, so the plan becomes an index scan that stops after 20 rows with no Sort node. PostgreSQL can scan a B-tree backwards, so the DESC markers matter only if the two sort columns ever disagree in direction; keeping them explicit documents the order the keyset cursor depends on.

Follow-up

• The endpoint paginates with OFFSET. What does page 500 cost with your index, and what does the keyset version cost?
• How would you have caught this before release, given that a 10,000-row seed database produces the same plan shape at an unnoticeable cost?

Suggested practice checklist

Built from the rounds and topics Morgan Lewis candidates report.

Day 1 — Map the Morgan Lewis loop

• Write out the reported sequence: HR Screening, Technical Interviews, Cultural Fit Assessment.
• 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 SQL

• Spend the session on SQL, which Morgan Lewis candidates report being tested on.
• Write one worked example in SQL and time yourself on it.

Deliverable: One timed worked example in SQL.

Day 3 — Work Problem Solving

• Spend the session on Problem Solving, which Morgan Lewis candidates report being tested on.
• Write one worked example in Problem Solving and time yourself on it.

Deliverable: One timed worked example in Problem Solving.

Day 4 — Work C#

• Spend the session on C#, which Morgan Lewis candidates report being tested on.
• Write one worked example in C# and time yourself on it.

Deliverable: One timed worked example in C#.

Day 5 — Answer out loud: Technical Questions

• Answer aloud, timed: Explain the difference between TCP and UDP protocols.
• Answer aloud, timed: How do you find the maximum difference between repeated elements in an array?

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

Day 6 — Answer out loud: System Design & Architecture

• Answer aloud, timed: How would you design a scalable system for managing legal documents?
• Answer aloud, timed: What are the key considerations when designing a microservices architecture?

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

Day 7 — Answer out loud: Behavioral Questions

• Answer aloud, timed: Describe a time you faced a challenge in a project and how you managed it.
• Answer aloud, timed: How do you prioritize tasks when working on multiple projects?

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

Behavioural preparation

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

Describe a time you faced a challenge in a project and how you managed it.

Medium · Behavioral Questions

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 prioritize tasks when working on multiple projects?

Medium · Behavioral Questions

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 ambiguity in project requirements?

Medium · Problem-Solving Questions

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?