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Tenica and Associates Software Engineer Interview Guide

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

The 60-second brief

At Tenica and Associates, a Software Engineer (including specialized tracks like Systems Engineer, Cyber Systems Engineer, and Software Developer) plays a pivotal role in safeguarding national security and optimizing enterprise-grade intelligence systems. Operating primarily within the defense and intelligence sectors, engineers at Tenica and Associates design, develop, secure, and maintain complex, large-scale systems that process critical information. The work is deeply integrated with federal agencies, demanding not only technical excellence but also a commitment to the mission-critical nature of the projects. The impact of this position is felt across national security infrastructures, where your code, system designs, and security implementations directly protect sensitive data assets.

This guide is scoped to a Software Engineer candidate at Tenica and Associates.

Focus areas

  • IT Network Engineering
  • Information Security Engineering
  • Cyber Systems Engineering

The Tenica and Associates interview process

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

Recruiter Call

Initial screening call with a recruiter to verify technical background, career goals, and security clearance status.

What to demonstrate

  • Initial screening call with a recruiter to verify technical background, career goals, and security clearance status
  • Depth in IT Network Engineering

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 Evaluations

Technical phone screen or virtual panel interview with senior engineers and program managers.

What to demonstrate

  • Technical phone screen or virtual panel interview with senior engineers and program managers
  • Depth in IT Network Engineering

How to prepare

  • Answer aloud and timed: Describe your process for debugging a memory leak in a production environment.
  • Answer aloud and timed: What is the difference between synchronous and asynchronous communication, and when would you use each?

Deep-Dive Discussions

In-depth technical discussions, architectural scenarios, and behavioral assessments to evaluate fit for government contracting.

What to demonstrate

  • In-depth technical discussions, architectural scenarios, and behavioral assessments to evaluate fit for government contracting
  • Depth in IT Network Engineering

How to prepare

  • Answer aloud and timed: How do you approach API versioning and backward compatibility when updating systems?
  • Answer aloud and timed: What are the key principles of the Risk Management Framework (RMF), and how do they apply to software development?

Where candidates lose points

Leverage the STAR Method

When answering behavioral questions, structure your responses using the Situation, Task, Action, and Result framework. Focus heavily on the Action you took and the quantifiable Result of your work.

Emphasize Security in Every Answer

Whether you are discussing database design, API integration, or system deployment, always mention how you incorporate security best practices into your engineering decisions.

Be Clear About Your Technical Boundaries

If you encounter a technical question or scenario you do not know, be honest. Explain how you would go about researching the solution, leveraging documentation, or consulting with specialists.

Demonstrate Mission Alignment

Show that you understand the unique responsibilities of supporting the Department of Defense and the Intelligence Community. Expressing a genuine commitment to the security mission resonates strongly with interviewers.

Questions & practice

What is the difference between synchronous and asynchronous communication, and when would you use each?

Medium · Systems & Software Engineering Fundament

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?

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?

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?

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?

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?

Explain the differences between microservices and monolithic architectures. What are the trade-offs in a secur

Medium · Systems & Software Engineering Fundament

Explain the differences between microservices and monolithic architectures. What are the trade-offs in a secure environment?

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 do you ensure high availability and disaster recovery in a distributed system?

Medium · Systems & Software Engineering Fundament

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 do you approach API versioning and backward compatibility when updating systems?

Medium · Systems & Software Engineering Fundament

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?

What are the key principles of the Risk Management Framework (RMF), and how do they apply to software developm

Medium · Cloud, Security & Infrastructure

What are the key principles of the Risk Management Framework (RMF), and how do they apply to software development?

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 design a secure cross-domain solution to transfer data between classified networks?

Medium · Cloud, Security & Infrastructure

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?

Explain the concept of Infrastructure as Code (IaC) and how you have used tools like Terraform or CloudFormati

Medium · Cloud, Security & Infrastructure

Explain the concept of Infrastructure as Code (IaC) and how you have used tools like Terraform or CloudFormation.

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 do you implement Zero Trust architecture principles within a cloud-native application?

Medium · Cloud, Security & Infrastructure

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?

Describe your process for debugging a memory leak in a production environment.

Medium · Systems & Software Engineering Fundament

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 Tenica and Associates candidates report.

Day 1 — Map the Tenica and Associates loop

  • Write out the reported sequence: Recruiter Call, Technical Evaluations, Deep-Dive Discussions.
  • 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 IT Network Engineering

  • Spend the session on IT Network Engineering, which Tenica and Associates candidates report being tested on.
  • Write one worked example in IT Network Engineering and time yourself on it.

Deliverable: One timed worked example in IT Network Engineering.

Day 3 — Work Information Security Engineering

  • Spend the session on Information Security Engineering, which Tenica and Associates candidates report being tested on.
  • Write one worked example in Information Security Engineering and time yourself on it.

Deliverable: One timed worked example in Information Security Engineering.

Day 4 — Work Cyber Systems Engineering

  • Spend the session on Cyber Systems Engineering, which Tenica and Associates candidates report being tested on.
  • Write one worked example in Cyber Systems Engineering and time yourself on it.

Deliverable: One timed worked example in Cyber Systems Engineering.

Day 5 — Answer out loud: Systems & Software Engineering Fundamentals

  • Answer aloud, timed: Explain the differences between microservices and monolithic architectures. What are the trade-offs in a secure environment?
  • Answer aloud, timed: How do you ensure high availability and disaster recovery in a distributed system?

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

Day 6 — Answer out loud: Cloud, Security & Infrastructure

  • Answer aloud, timed: What are the key principles of the Risk Management Framework (RMF), and how do they apply to software development?
  • Answer aloud, timed: How would you design a secure cross-domain solution to transfer data between classified networks?

Deliverable: Spoken answers to 2 reported Cloud, Security & Infrastructure question(s), under time.

Day 7 — Answer out loud: Behavioral & Mission Alignment

  • Answer aloud, timed: Describe a time when you had to deliver a technical solution with highly ambiguous requirements. How did you proceed?
  • Answer aloud, timed: How do you manage technical debt when working under tight federal compliance deadlines?

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

Behavioural preparation

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

Describe your experience with containerization (Docker) and orchestration (Kubernetes) in a secure, air-gapped

Medium · Cloud, Security & Infrastructure

Describe your experience with containerization (Docker) and orchestration (Kubernetes) in a secure, air-gapped 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 time when you had to deliver a technical solution with highly ambiguous requirements. How did you p

Medium · Behavioral & Mission Alignment

Describe a time when you had to deliver a technical solution with highly ambiguous requirements. How did you proceed?

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 technical debt when working under tight federal compliance deadlines?

Medium · Behavioral & Mission 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?

Talk about a time you disagreed with a systems architect or senior stakeholder. How did you resolve the confli

Medium · Behavioral & Mission Alignment

Talk about a time you disagreed with a systems architect or senior stakeholder. How did you resolve the conflict?

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 stay updated with emerging technologies and security standards relevant to the intelligence communi

Medium · Behavioral & Mission Alignment

How do you stay updated with emerging technologies and security standards relevant to the intelligence community?

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 critical system failed under your watch. What immediate steps did you take, and w

Medium · Behavioral & Mission Alignment

Describe a situation where a critical system failed under your watch. What immediate steps did you take, and what was the long-term resolution?

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?