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American National Insurance Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at American National Insurance, you play a foundational role in building, maintaining, and scaling the technological infrastructure that powers a multi-line insurance corporation. Your work directly supports critical business operations, customer-facing applications, and enterprise integration solutions that have provided financial security and stability for generations of policyholders. Whether you are modernizing core digital workflows, designing high-performing APIs, or managing complex enterprise systems, your contributions ensure that the organization remains agile, secure, and technologically competitive. This position bridges the gap between complex business logic and robust technical execution.

This guide is scoped to a Software Engineer candidate at American National Insurance.

Focus areas

  • z/OS
  • Mainframe Support
  • z/OS Systems Programming

The American National Insurance interview process

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

Initial Screening

Screening by a recruiter to verify background and alignment with role logistics.

What to demonstrate

  • Screening by a recruiter to verify background and alignment with role logistics
  • Depth in z/OS

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

Series of technical interviews focusing on specific domain expertise and past projects.

What to demonstrate

  • Series of technical interviews focusing on specific domain expertise and past projects
  • Depth in z/OS

How to prepare

  • Answer aloud and timed: Can you explain your experience with enterprise integration patterns and data transformations across XML and JSON formats?
  • Answer aloud and timed: What is your familiarity with message-oriented middleware, IBM integration platforms, or z/OS systems programming?

Behavioral Questions

Discussion of behavioral scenarios to assess cultural fit and collaboration skills.

What to demonstrate

  • Discussion of behavioral scenarios to assess cultural fit and collaboration skills
  • Depth in z/OS

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 questions above and write down what you would ask to confirm before it.

Panel Interview

Conversation with hiring manager and peers to evaluate technical and interpersonal skills.

What to demonstrate

  • Conversation with hiring manager and peers to evaluate technical and interpersonal skills
  • Depth in z/OS

How to prepare

  • Answer aloud and timed: Tell me about a time you faced a significant technical challenge or bottleneck, and how you worked through it.
  • Answer aloud and timed: How do you handle workplace adaptability and shifting priorities within an Agile or Scrum delivery environment?

Where candidates lose points

Highlight business impact

When discussing past technical projects, always tie your engineering decisions back to user outcomes, system reliability, or operational efficiency.

Embrace the STAR method

Structure your behavioral responses using the Situation, Task, Action, Result framework to keep your stories concise, focused, and impactful.

Showcase adaptability

Insurance and financial technology environments often balance modern architectures with legacy systems; emphasize your ability to navigate legacy codebases with patience and analytical rigor.

Prepare thoughtful questions

Ask your interviewers about team culture, deployment cadences, and how engineering priorities are balanced with business demands to show genuine engagement.

Demonstrate alignment with core values

Familiarize yourself with the company's foundational principles and weave examples of integrity, teamwork, and service into your behavioral answers.

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?

Collapse a redelivered event batch into per-aggregate high-water marks

Easy · hashing · at-least-once · aggregation

You drain a batch of up to 5,000,000 events, each (aggregate_id BIGINT, aggregate_version INT, event_type, payload). The log guarantees order within one aggregate only; the batch merges 64 partitions, and a relay failover has redelivered a range, so an older version for an aggregate can appear after a newer one. Given a map of last_applied_version per aggregate, produce the events worth applying, at most one per (aggregate_id, version), plus the count discarded. Target O(n) time. State the memory for 2,000,000 distinct aggregates and what you do when it does not fit.

Approach

  1. One pass, one hash map from aggregate_id to the highest version kept, and a discard counter. An event whose version is at or below last_applied_version for its aggregate is dropped without further work, which is the whole reason the event carries its version rather than a delta. O(n) expected time, O(d) space in distinct aggregates.
  2. Keep the maximum, never the last occurrence. The redelivered range means the final appearance of an aggregate in the batch can be an older version than one seen earlier in the same batch, so last-wins applies stale state over newer state and the projection regresses with no error anywhere.
  3. Cost the memory instead of calling it large: an 8-byte key plus a 4-byte version is 12 bytes of payload, and an open-addressed table held at a 0.7 load factor costs roughly 17 bytes per entry before per-slot metadata, so 2,000,000 aggregates is tens of megabytes in a native layout and several times that in a runtime that boxes both key and value.
  4. If the distinct set exceeds memory, partition on hash(aggregate_id) mod P and reduce each partition independently. Every event for one aggregate hashes to the same partition, so the per-partition result is exact and the merge is concatenation rather than a second reduction.

Follow-up

  • The payload is a patch rather than a snapshot, so applying only the highest version loses the intermediate changes. What changes in your reduction?
  • How do you detect that version 7 arrived while version 6 was never delivered, and what should the consumer do about the gap?

Track a rolling failure rate per destination for circuit decisions

Easy · sliding window · ring buffer · circuit breaker

The egress service delivers about 1,500 webhooks per second across roughly 40,000 destinations, each call bounded by a 10 second timeout. Maintain, per destination, the failure rate over the trailing 60 seconds so a caller can ask before dispatch whether the circuit should open. Attempts arrive as (destination_id, finished_at_ms, outcome). Requirement: amortised O(1) per attempt, with total memory bounded by the destination count rather than by traffic. Give the structure, its exact memory, and the rule that stops a destination with three attempts from opening a circuit.

Approach

  1. Name the exact-deque version and then reject it as the default. Holding timestamps and advancing a tail pointer past anything older than now minus 60 seconds is a correct two-pointer window at amortised O(1) per attempt, but its memory tracks in-window traffic, so one destination in a retry storm holds hundreds of thousands of entries while thousands of quiet destinations hold none.
  2. Use a ring of 60 one-second buckets per destination, each bucket a pair of counters for attempts and failures. On an attempt, advance the ring by the elapsed whole seconds, zeroing at most min(elapsed, 60) buckets, then increment the head. That is amortised O(1) with a fixed footprint per destination.
  3. State the footprint: 60 buckets times two 4-byte counters is 480 bytes of payload per destination, so 40,000 destinations is roughly 20 to 25 MB with per-entry overhead, bounded by the catalogue rather than by the rate. The cost is granularity, since the oldest bucket ages out in whole seconds, which is far tighter than the decision needs.
  4. Require a minimum sample before the circuit may open. A destination with three attempts and three failures reads as 100 percent and is not evidence; a floor of roughly 20 attempts in the window makes the ratio meaningful, and below that floor use a run of consecutive failures as the trigger instead.

Follow-up

  • The fleet is 30 instances and each sees roughly a thirtieth of a destination's traffic. Where does the rate actually live, and what does a per-instance answer get wrong?
  • A destination answers in 9.5 seconds and succeeds. It is not failing but it is consuming your per-destination concurrency. What signal should open the circuit here?

Write the update path that detects a concurrent edit

Medium · optimistic concurrency · transactional outbox · audit history

resource carries version INT NOT NULL DEFAULT 1. resource_revision holds revision_id, resource_id, version, actor_user_id, change_kind, patch JSONB, request_id, created_at with UNIQUE (resource_id, version). outbox_event holds aggregate_type, aggregate_id, aggregate_version, event_type, payload, status. A PUT carries the version the client read. Write the exact statements for the single transaction that applies the edit, records the revision and enqueues 'resource.updated', and give the handler's branch on zero affected rows. Then say what PostgreSQL 16 does under READ COMMITTED when two of these updates hit one row at once.

Approach

  1. One transaction, three writes, no network call inside it: UPDATE resource SET title = $3, version = version + 1, updated_at = now() WHERE resource_id = $1 AND tenant_id = $4 AND version = $2; then INSERT the resource_revision row at version $2 + 1; then INSERT the outbox_event row at the same aggregate_version. The event goes to a table rather than a broker because no transaction spans both.
  2. Branch on the affected-row count before doing anything else. Zero has three causes — stale version, wrong tenant, row gone — so re-read once and map to 409 carrying the current version, or 404 for an id outside the caller's tenant, which also stops the endpoint confirming that another tenant's id exists.
  3. State the engine behaviour instead of assuming it. Under READ COMMITTED the second UPDATE blocks on the row lock, and when the first commits PostgreSQL re-evaluates the WHERE clause against the newly committed row, so the version predicate now fails and the statement reports zero rows. Under REPEATABLE READ the identical collision raises SQLSTATE 40001 instead, so the handler must fold both shapes into one conflict response.
  4. Keep UNIQUE (resource_id, version) even though the predicate already serialises writers. It is what makes a lost update unwritable if any other path ever reaches the revision table, and it converts a logic bug into 23505 rather than into a silently missing history row.

Follow-up

  • A client sends the version it read ten minutes ago and the resource has moved three versions. What is in your 409 so it can resolve the conflict without a full re-fetch?
  • Two editors, two disjoint fields, no overlap. Does your answer still refuse the second write, and should it?

Keep soft-deleted accounts from blocking re-registration

Easy · soft delete · unique constraints · engine differences

app_user holds user_id, tenant_id, email CITEXT, password_hash (NULL for SSO principals), email_verified_at, auth_version, status ('invited','active','suspended','deactivated'), created_at, updated_at, deleted_at. Two live accounts for one address inside a tenant must be impossible, but an address freed by a soft delete must be reusable, and the same tenant may delete and re-register it repeatedly. Write the uniqueness DDL for PostgreSQL 16, then the equivalent for MySQL 8 where partial indexes do not exist, and say what each permits once three deleted rows already hold that address.

Approach

  1. Start from what is actually unique: not (tenant_id, email), but (tenant_id, email) among live rows. PostgreSQL says that directly — CREATE UNIQUE INDEX app_user_live_email ON app_user (tenant_id, email) WHERE deleted_at IS NULL. A full constraint over the same two columns burns the address permanently the first time someone deletes an account.
  2. Keep case-insensitivity in the type or the index, never in the application: CITEXT as given, or UNIQUE (tenant_id, lower(email)) as an expression index where the extension is unavailable. A case-sensitive unique column is exactly how two accounts for one human appear.
  3. For MySQL 8 the predicate has to move inside the key: add a discriminator column that is a constant 0 while the row is live and is set to user_id on delete, with UNIQUE (tenant_id, email, deleted_marker). Live rows share the constant and still collide; deleted rows differ from each other and stop colliding.
  4. State the NULL variant and its dependency: leaving the marker NULL for deleted rows also works, because a unique index treats NULLs as distinct — true in MySQL, and true in PostgreSQL only under the default NULLS DISTINCT, which PostgreSQL 15 lets you reverse. Check the polarity against the three existing deleted rows: constant-on-live is what preserves the collision you want, and reversing it silently admits duplicate live accounts.

Follow-up

  • A deleted account re-registers with the same address the next day. Do the old resource rows follow the new user_id, and how does the API keep the two principals apart?
  • How do you honour an erasure request while resource_revision.actor_user_id still references this table?

How do you approach designing and implementing secure RESTful and SOAP-based web services or APIs?

Medium · Technical and Domain Knowledge

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 your familiarity with message-oriented middleware, IBM integration platforms, or z/OS systems programm

Medium · Technical and Domain Knowledge

What is your familiarity with message-oriented middleware, IBM integration platforms, or z/OS systems programming?

Approach

  1. Say who the caller is and what they do when the call fails halfway.
  2. Define the identity of a request so a retry cannot double-apply it.
  3. Separate accepted, pending, failed and confirmed; they are different facts.
  4. 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?

How do you approach daily responsibilities, task prioritization, and time management in a fast-paced environme

Medium · Process and Methodology

How do you approach daily responsibilities, task prioritization, and time management in a fast-paced environment?

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 do you ensure traceability and rollback capabilities when designing and implementing CI/CD pipelines?

Medium · Process and Methodology

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 do you manage support tickets, incident escalations, and urgent operational requests using tools like Serv

Medium · Process and Methodology

How do you manage support tickets, incident escalations, and urgent operational requests using tools like ServiceNow?

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 strategies do you use for technical estimations and providing architectural input on scalability and tool

Medium · Process and Methodology

What strategies do you use for technical estimations and providing architectural input on scalability and tooling?

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?

Exports duplicate a row range about once a week

Hard · leases · clock skew · idempotency

Roughly once a week an export writes a file containing a duplicated range of rows. The affected job_run rows show attempt = 1, status = succeeded, one started_at, and a lease_owner naming a different host from the one whose logs show the job starting. Leases last 30 seconds and are heartbeated every 10 from inside the handler; lease_expires_at is computed on the worker and compared against the database's now(). Find the mechanism, and give a fix that holds even if you cannot fix the clocks.

Approach

  1. Start from the fact that eliminates the obvious answer. attempt = 1 means no retry was recorded, so this is not a re-run after failure; two workers ran the same row concurrently and the takeover path never touched the counter. lease_owner naming a host other than the one that started the job is the same statement from the other side.
  2. Enumerate the mechanisms that cause a premature takeover, then find the signal that separates them. Either the lease genuinely expired because the heartbeat did not fire, which is what happens when the heartbeat runs on the handler's own thread and the handler makes a long blocking call, or it only appeared expired because two clocks disagree, since lease_expires_at is written from the worker's clock and evaluated against the database's. The discriminator is the distribution: incidents clustered on the longest exports indict the heartbeat, incidents clustered on one host indict skew. Measure both, and measure each host's offset against the database directly.
  3. Read the reclaim query precisely. In PostgreSQL now() is transaction start time, not statement time, so a reclaimer holding a long transaction compares against an older timestamp than expected; clock_timestamp() is the statement-time function. This is worth ruling in or out before you redesign anything, because it changes which rows look expired.
  4. Remove the second clock rather than trying to synchronise it. Issue and extend the lease in the database, with lease_expires_at = now() + interval '30 seconds' in both the claim and the heartbeat, so exactly one clock is ever compared and worker skew stops mattering to this predicate.

Follow-up

  • The displaced worker has already streamed half the file to object storage. What makes that side effect safe to repeat?
  • You now count takeovers. What alert fires on that counter, and at what threshold?

Suggested practice checklist

Built from the rounds and topics American National Insurance candidates report.

Day 1 — Map the American National Insurance loop

  • Write out the reported sequence: Initial Screening, Technical Interviews, Behavioral Questions, Panel Interview.
  • 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 z/OS

  • Spend the session on z/OS, which American National Insurance candidates report being tested on.
  • Write one worked example in z/OS and time yourself on it.

Deliverable: One timed worked example in z/OS.

Day 3 — Work Mainframe Support

  • Spend the session on Mainframe Support, which American National Insurance candidates report being tested on.
  • Write one worked example in Mainframe Support and time yourself on it.

Deliverable: One timed worked example in Mainframe Support.

Day 4 — Work z/OS Systems Programming

  • Spend the session on z/OS Systems Programming, which American National Insurance candidates report being tested on.
  • Write one worked example in z/OS Systems Programming and time yourself on it.

Deliverable: One timed worked example in z/OS Systems Programming.

Day 5 — Answer out loud: Technical and Domain Knowledge

  • Answer aloud, timed: What has been your experience working with object-oriented programming languages like Java,.NET, Go, or JavaScript?
  • Answer aloud, timed: How do you approach designing and implementing secure RESTful and SOAP-based web services or APIs?

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

Day 6 — Answer out loud: Behavioral and Culture Fit

  • Answer aloud, timed: Can you walk me through your background, past projects, and your primary career goals?
  • Answer aloud, timed: Tell me about a time you faced a significant technical challenge or bottleneck, and how you worked through it.

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

Day 7 — Answer out loud: Process and Methodology

  • Answer aloud, timed: How do you approach daily responsibilities, task prioritization, and time management in a fast-paced environment?
  • Answer aloud, timed: What has been your experience participating in Agile ceremonies such as sprint planning, retrospectives, and backlog grooming?

Deliverable: Spoken answers to 2 reported Process and Methodology question(s), under time.

Behavioural preparation

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

What has been your experience working with object-oriented programming languages like Java,.NET, Go, or JavaSc

Medium · Technical and Domain Knowledge

What has been your experience working with object-oriented programming languages like Java,.NET, Go, or JavaScript?

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?

Can you explain your experience with enterprise integration patterns and data transformations across XML and J

Medium · Technical and Domain Knowledge

Can you explain your experience with enterprise integration patterns and data transformations across XML and JSON formats?

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 performance tuning, troubleshooting, and resolving complex integration issues across distrib

Medium · Technical and Domain Knowledge

How do you handle performance tuning, troubleshooting, and resolving complex integration issues across distributed systems?

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?

Can you walk me through your background, past projects, and your primary career goals?

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?

Tell me about a time you faced a significant technical challenge or bottleneck, and how you worked through it.

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?

How do you handle workplace adaptability and shifting priorities within an Agile or Scrum delivery environment

Medium · Behavioral and Culture Fit

How do you handle workplace adaptability and shifting priorities within an Agile or Scrum delivery environment?

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 situation where you had to collaborate closely with a cross-functional team or non-technical stakeh

Medium · Behavioral and Culture Fit

Describe a situation where you had to collaborate closely with a cross-functional team or non-technical stakeholders.

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?

What does teamwork mean to you, and how do you contribute to a positive and inclusive engineering culture?

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?

What has been your experience participating in Agile ceremonies such as sprint planning, retrospectives, and b

Medium · Process and Methodology

What has been your experience participating in Agile ceremonies such as sprint planning, retrospectives, and backlog grooming?

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?