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Integrated Talent Strategies (Its) Software Engineer Interview Guide

Integrated Talent Strategies (Its) Software Engineer interview guide: reported rounds, questions and how candidates describe the process.

The 60-second brief

At Integrated Talent Strategies (ITS), technical roles like Software Engineer span a diverse spectrum of specialized engineering disciplines. As a premier technical staffing and recruitment firm, Integrated Talent Strategies (ITS) partners with leading manufacturing, automotive, industrial, and construction companies to deploy highly skilled engineering professionals. In this ecosystem, a Software Engineer or systems-focused engineer is responsible for bridging the gap between physical machinery, industrial software, and automation systems. Your work directly impacts production efficiency, quality control, and system reliability for major enterprise clients.

This guide is scoped to a Software Engineer candidate at Integrated Talent Strategies (Its).

Focus areas

  • Software Engineering (General)
  • Metrology Engineering
  • CMM Engineering (Coordinate Measuring Machines)

The Integrated Talent Strategies (Its) interview process

Integrated Talent Strategies (Its) candidates report 4 rounds over 3-5 weeks. The stages below are what candidates describe, not a published process.

Initial Consultation

Begin with a consultation with an ITS technical recruiter to align career goals and technical capabilities.

What to demonstrate

  • Begin with a consultation with an ITS technical recruiter to align career goals and technical capabilities
  • Depth in Software Engineering (General)

How to prepare

  • Answer aloud and timed: How do you approach programming a complex 3D part using PC-DMIS or Calypso software?
  • Answer aloud and timed: Describe your experience with GD&T (Geometric Dimensioning and Tolerancing) and how you translate engineering drawings into measurement programs.

Technical Evaluation

Participate in a deeper technical evaluation or interview with an account manager.

What to demonstrate

  • Participate in a deeper technical evaluation or interview with an account manager
  • Depth in Software Engineering (General)

How to prepare

  • Answer aloud and timed: What steps do you take when a CMM measurement program reports a critical dimensional deviation that conflicts with physical measurements?
  • Answer aloud and timed: How do you handle file management and version control for measurement programs across multiple manufacturing shifts?

Client Presentation

Once cleared through internal screening, candidates are presented to the end client for final interviews.

What to demonstrate

  • Once cleared through internal screening, candidates are presented to the end client for final interviews
  • Depth in Software Engineering (General)

How to prepare

  • Answer aloud and timed: Explain how you calibrate a probe changer and ensure probe matrix accuracy before a high-volume production run.
  • Answer aloud and timed: Explain your process for troubleshooting a sudden PLC communication failure on an active assembly line.

Final Client Interviews

Engage in final interviews with the client, focusing on technical domain and behavioral assessment.

What to demonstrate

  • Engage in final interviews with the client
  • Focusing on technical domain and behavioral assessment

How to prepare

  • Answer aloud and timed: Describe a time you had to modify existing ladder logic code to optimize a machine's cycle time.
  • Answer aloud and timed: How do you utilize SCADA or HMI software to diagnose intermittent hardware faults?

Where candidates lose points

Highlight your adaptability

Clients value engineers who can walk onto a plant floor, quickly assess a situation, and adapt to the existing software systems and team dynamics.

Bring a portfolio or project list

If permitted, bring a brief, non-proprietary list of projects, CMM programs, or automation systems you have successfully configured or optimized in the past.

Never share proprietary code, confidential client blueprints, or sensitive manufacturing data during your interviews

Focus on your methodology, general techniques, and personal contributions instead.

Align with client values

Ask your ITS recruiter about the specific client's culture (e.g., highly focused on safety, rapid production scaling, or rigorous quality metrics) and tailor your behavioral answers to match those priorities.

Questions & practice

Merge partitioned event streams into one ordered feed with bounded lateness

Hard · k-way merge · watermarks · out-of-order streams

The read-model service consumes 64 log partitions carrying about 4,000 events per second in total. Each partition is ordered within itself, but partitions drift by up to 30 seconds, and the activity feed must present a tenant's events in occurred_at order. Produce the merge. State its complexity, the buffer it requires in events and in bytes, what happens when one partition is idle, and what you do with an event that arrives after you have already emitted its position. Payloads average 1 KB.

Approach

  1. Merge with a min-heap over the 64 partition heads keyed on (occurred_at, event_id): O(log P) per event and O(n log P) overall. The tie-break on event_id is what makes the output deterministic when two partitions carry the same millisecond, which matters because the feed is paginated and a non-deterministic order reorders pages under the reader.
  2. Emitting the heap head is only correct once every partition has produced everything up to that timestamp, so the emit condition is a watermark: the minimum across partitions of the highest occurred_at seen, less the allowed lateness. Events are held until the watermark passes them, which is what turns individually ordered streams into a jointly ordered one.
  3. Size the buffer from the lateness rather than guessing: 4,000 events per second times 30 seconds is 120,000 buffered events, and at 1 KB each about 120 MB of heap. That number is the real price of the ordering guarantee and belongs in front of whoever asked for it.
  4. Handle the idle partition explicitly, because it fails the feed rather than corrupting it: a partition with no traffic never advances its own maximum, so the watermark freezes and output stops entirely. Either every partition emits a periodic idle marker carrying the broker's current time, or the watermark falls back to wall clock for a partition silent beyond a threshold.

Follow-up

  • The lateness budget is raised to five minutes. What is the new buffer, and what besides memory changes?
  • The consumer restarts. Where does it resume from, and what does the feed look like for the first 30 seconds?

Diff a projection against the primary without per-row point reads

Hard · reconciliation · range hashing · throttling

The listing projection has drifted and some rows show a stale version. The primary holds 40,000,000 resource rows across 12,000 tenants while serving 1,200 writes and 14,000 reads per second. The obvious repair, reading each resource row and comparing its version against the projection, is correct and would eventually finish. Explain precisely why it is unacceptable here, then give a diff that finds the differing rows, state its complexity, and make it safe to run against a live primary. Replication lag is usually under 100 ms and is not bounded.

Approach

  1. Quantify the naive cost rather than calling it slow: 40,000,000 point reads at even 0.5 ms each is over five hours serialised, and the only lever is concurrency, which is exactly what you cannot spend. The primary's pool is sized for the write path, and 40,000,000 random reads evict the buffer cache that sustains the 85 percent cache hit rate, so the audit degrades the system it is auditing.
  2. Replace random access with one ordered pass per side. Both sides can be read in (tenant_id, resource_id) order, which is a sequential scan on each and a merge join in O(n) time and O(1) memory. For a dense diff that is the whole answer, and it reads the primary once instead of 40,000,000 times.
  3. For the expected sparse case, compare range hashes instead of rows: partition the key space, compute per range an order-independent aggregate over hash(resource_id, version), compare aggregates, and descend only into ranges that differ. With d differing rows and branching factor B, at most d ranges mismatch per level, so the drill-down examines O(d log_B(n/d)) ranges and reads full rows only in mismatching leaves.
  4. Aggregate with a sum modulo 2^64 or a multiset hash, never XOR. XOR is order-independent but self-cancelling, so two rows wrong in the same way, or a row duplicated on one side, leave the range aggregate matching and the range is declared clean.

Follow-up

  • The diff reports 900 stale rows. How do you decide between patching those rows and rebuilding the projection from resource_revision?
  • Same job, but the projection lives in a search index that cannot be scanned in key order. What changes?

Archive a resource graph without breaking live references or recursing

Medium · graph traversal · topological order · tenant isolation

Resources reference other resources within a tenant; for the largest tenant the reference table holds up to 2,000,000 nodes and 8,000,000 edges. Archiving a resource must archive everything reachable from it that nothing outside the set still references, refuse when a live external referrer exists, and terminate when references form cycles, which they legitimately do. Produce the archive order and the refusal list, targeting O(V+E). Say what stops the traversal crossing a tenant boundary, and why recursion is the wrong control structure at this size.

Approach

  1. Load the subgraph with the tenant predicate on both endpoints of the edge, not only on the side you started from. Scoping the left table alone is the classic cross-tenant leak: one mis-entered edge then pulls another tenant's resources into the traversal and, worse, into the archive.
  2. Traverse iteratively with an explicit stack. A 2,000,000-node graph can hold a chain deep enough to exhaust a native stack in the low tens of thousands of frames, and that failure is a process crash rather than an error you can return.
  3. Treat cycles as data rather than corruption: compute strongly connected components with Tarjan in O(V+E) using its own explicit stack, then condense. The condensation is a DAG, so a topological order over it gives the archive order, and every member of a component archives in one transaction because no order within a cycle is valid.
  4. Decide refusals with reverse edges. A candidate is archivable only if every in-edge originates inside the candidate set, so build the transpose or count in-degrees restricted to the visited set, and emit each blocked resource with the id of the external referrer, which is the only part of the answer an operator can act on.

Follow-up

  • The graph is read in one query and the archive writes a minute later. What can change in between, and how do you make the write safe?
  • The candidate set is 400,000 resources. Is that one transaction, and if not, what does a half-finished archive look like to a reader?

Stop tag and share joins from fanning out a page

Medium · join fan-out · semi-joins · many-to-many

resource_tag is (resource_id, tag_id) with PK (resource_id, tag_id); resource_share is (resource_id, shared_with_user_id, permission). The tagged-and-shared listing inner-joins resource to both, filters tenant_id, tag_id = ANY($2) and shared_with_user_id = $3, orders by updated_at DESC and takes 50. Pages come back with fewer than 50 distinct resources and the total in the header is far too high. Explain the row multiplication, rewrite both the page query and the count query so each is correct, and name the index each one needs. PostgreSQL 16.

Approach

  1. Do the arithmetic against the predicates that are actually there. An inner join emits one row per matching child row, and both joins are filtered: tag_id = ANY($2) admits only the requested tags, shared_with_user_id = $3 admits one user's share rows. So a resource holding three of the requested tags and shared with $3 once yields three rows, not one — the multiplier is its count of matching tags times its share rows for that single user, and that second factor is 1 unless the table admits duplicate (resource_id, shared_with_user_id) pairs. LIMIT 50 then limits rows rather than resources, and COUNT(*) counts pairs — the header is the product, not the population.
  2. Reject DISTINCT as the fix. It deduplicates after the product has been built, so the planner must materialise and sort the fanned-out set before the LIMIT can apply, and it leaves any SUM or AVG in the same select list wrong.
  3. Rewrite both filters as semi-joins, keeping resource as the only row source: AND EXISTS (SELECT 1 FROM resource_tag rt WHERE rt.resource_id = r.resource_id AND rt.tag_id = ANY($2)) and the same shape against resource_share. A semi-join stops at the first match per resource and preserves the driving index order, so ORDER BY updated_at DESC, resource_id DESC LIMIT 50 still stops after 50 rows.
  4. Count with the same predicates and no join at all: SELECT count(*) FROM resource r WHERE r.tenant_id = $1 AND r.status = 'active' AND EXISTS (...) AND EXISTS (...). Nothing multiplies a resource, so the number is the population.

Follow-up

  • The filter changes from 'any of these tags' to 'all of these tags'. Rewrite it and state what it costs relative to the ANY form.
  • A resource can be shared with the same user twice under different permissions. Does your count change, and should it?

Replace offset paging on the resource feed with keyset

Easy · keyset pagination · composite index · sort order

resource holds resource_id, tenant_id, owner_user_id, title, body_ref, version, status ('draft','active','archived','deleted'), created_at, updated_at, deleted_at, with an index on (tenant_id, status, updated_at DESC, resource_id DESC). The listing endpoint returns active resources for one tenant, newest update first, 50 per page, today with LIMIT 50 OFFSET n. Tenants reach page 400 and rows are created while they read. Write the keyset query, define what the cursor carries and how it is encoded, and say which part of the index each predicate uses. Assume PostgreSQL 16.

Approach

  1. Name the two failures separately. OFFSET 20000 makes the server produce and discard 20,000 rows, so page cost grows with depth rather than with page size. Independently, any write that changes how many rows sort above the offset moves the window between two fetches, and the direction decides which anomaly you get: an insert lands at the head of updated_at DESC and pushes already-returned rows down past the boundary, so they are returned a second time; a delete above the offset, or a row whose updated_at is bumped above the cursor, pulls rows up and one is never returned at all. Nothing in the response reveals either.
  2. Write the seek: WHERE tenant_id = $1 AND status = 'active' AND (updated_at, resource_id) < ($2, $3) ORDER BY updated_at DESC, resource_id DESC LIMIT 50. The row-value comparison is one index range rather than a disjunction, and both columns are NOT NULL, which is what makes that comparison well defined.
  3. Map each predicate onto the index: tenant_id and status are equality on the leading columns, (updated_at, resource_id) is the range, and the ORDER BY matches the index order so no Sort node appears and the scan stops after 50 rows. The DESC in the definition only matters for mixed directions — a plain ascending btree on the same columns is read backwards for this query.
  4. Put both sort columns in the cursor and nothing the client can tamper with into another tenant: base64 of (updated_at, resource_id), validated server-side, with tenant_id taken from the principal.

Follow-up

  • The client asks for 'jump to page 400'. What do you offer instead, and what does the honest version cost?
  • Sort order becomes user-selectable across four columns. How many indexes is that, and which would you refuse to add?

How do you approach programming a complex 3D part using PC-DMIS or Calypso software?

Medium · Metrology & CMM Software Engineering

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?

Explain how you calibrate a probe changer and ensure probe matrix accuracy before a high-volume production run

Medium · Metrology & CMM Software Engineering

Explain how you calibrate a probe changer and ensure probe matrix accuracy before a high-volume production run.

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 safety protocols (like Lockout/Tagout) are integrated into your software testing workflows o

Medium · Maintenance & Automation Engineering

How do you ensure safety protocols (like Lockout/Tagout) are integrated into your software testing workflows on the plant floor?

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?

Explain your process for troubleshooting a sudden PLC communication failure on an active assembly line.

Medium · Maintenance & Automation Engineering

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?

How do you utilize SCADA or HMI software to diagnose intermittent hardware faults?

Medium · Maintenance & Automation Engineering

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 Integrated Talent Strategies (Its) candidates report.

Day 1 — Map the Integrated Talent Strategies (Its) loop

  • Write out the reported sequence: Initial Consultation, Technical Evaluation, Client Presentation, Final Client 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 4 reported rounds, with the weakest marked.

Day 2 — Work Software Engineering (General)

  • Spend the session on Software Engineering (General), which Integrated Talent Strategies (Its) 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 3 — Work Metrology Engineering

  • Spend the session on Metrology Engineering, which Integrated Talent Strategies (Its) candidates report being tested on.
  • Write one worked example in Metrology Engineering and time yourself on it.

Deliverable: One timed worked example in Metrology Engineering.

Day 4 — Work CMM Engineering (Coordinate Measuring Machines)

  • Spend the session on CMM Engineering (Coordinate Measuring Machines), which Integrated Talent Strategies (Its) candidates report being tested on.
  • Write one worked example in CMM Engineering (Coordinate Measuring Machines) and time yourself on it.

Deliverable: One timed worked example in CMM Engineering (Coordinate Measuring Machines).

Day 5 — Answer out loud: Metrology & CMM Software Engineering

  • Answer aloud, timed: How do you approach programming a complex 3D part using PC-DMIS or Calypso software?
  • Answer aloud, timed: Describe your experience with GD&T (Geometric Dimensioning and Tolerancing) and how you translate engineering drawings into measurement programs.

Deliverable: Spoken answers to 2 reported Metrology & CMM Software Engineering question(s), under time.

Day 6 — Answer out loud: Maintenance & Automation Engineering

  • Answer aloud, timed: Explain your process for troubleshooting a sudden PLC communication failure on an active assembly line.
  • Answer aloud, timed: Describe a time you had to modify existing ladder logic code to optimize a machine's cycle time.

Deliverable: Spoken answers to 2 reported Maintenance & Automation Engineering question(s), under time.

Day 7 — Answer out loud: Behavioral & Client-Facing Scenarios

  • Answer aloud, timed: Describe a situation where a client or stakeholder disagreed with your technical recommendations. How did you resolve it?
  • Answer aloud, timed: How do you prioritize your workload when multiple critical machines or systems go offline simultaneously?

Deliverable: Spoken answers to 2 reported Behavioral & Client-Facing Scenarios question(s), under time.

Behavioural preparation

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

Describe your experience with GD&T (Geometric Dimensioning and Tolerancing) and how you translate engineering

Medium · Metrology & CMM Software Engineering

Describe your experience with GD&T (Geometric Dimensioning and Tolerancing) and how you translate engineering drawings into measurement programs.

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 steps do you take when a CMM measurement program reports a critical dimensional deviation that conflicts

Medium · Metrology & CMM Software Engineering

What steps do you take when a CMM measurement program reports a critical dimensional deviation that conflicts with physical measurements?

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 file management and version control for measurement programs across multiple manufacturing s

Medium · Metrology & CMM Software Engineering

How do you handle file management and version control for measurement programs across multiple manufacturing shifts?

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 you had to modify existing ladder logic code to optimize a machine's cycle time.

Medium · Maintenance & Automation Engineering

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 is your experience with preventative maintenance software (CMMS) and how do you track machine reliability

Medium · Maintenance & Automation Engineering

What is your experience with preventative maintenance software (CMMS) and how do you track machine reliability metrics?

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 a client or stakeholder disagreed with your technical recommendations. How did you

Medium · Behavioral & Client-Facing Scenarios

Describe a situation where a client or stakeholder disagreed with your technical recommendations. 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 prioritize your workload when multiple critical machines or systems go offline simultaneously?

Medium · Behavioral & Client-Facing Scenarios

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?

Talk about a time you had to learn a proprietary software tool or system on a very tight timeline to complete

Medium · Behavioral & Client-Facing Scenarios

Talk about a time you had to learn a proprietary software tool or system on a very tight timeline to complete a project.

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 communicate highly technical software or calibration issues to non-technical plant managers or oper

Medium · Behavioral & Client-Facing Scenarios

How do you communicate highly technical software or calibration issues to non-technical plant managers or operators?

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?