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Impiricus Software Engineer Interview Guide

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

The 60-second brief

As a Software Engineer at Impiricus, you are joining the team behind the world’s first AI-powered HCP Engagement Engine. Named the #1 fastest-growing company in North America by the 2025 Deloitte Fast 500, Impiricus is at the intersection of cutting-edge technology and critical healthcare infrastructure. Your work directly impacts how life sciences companies support physicians, ensuring that evidence-based resources reach the hands of those who need them to improve patient outcomes. In this role, you will contribute to a high-scale, AI-driven ecosystem. Whether you are building robust backend services or refining full-stack experiences, you are working to solve complex problems within a deeply regulated and ethically grounded environment. You will collaborate with a multidisciplinary team to turn clinical insights into reliable, real-time digital channels.

This guide is scoped to a Software Engineer candidate at Impiricus.

Focus areas

  • System Design
  • Backend Architecture
  • Python

The Impiricus interview process

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

Recruiter Screen

Initial interaction focusing on your background, interest in the company, and basic logistics.

What to demonstrate

  • Initial interaction focusing on your background, interest in the company, and basic logistics
  • Depth in System Design

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 Assessment

Engagement in a technical assessment, which may include a take-home component or live coding.

What to demonstrate

  • Engagement in a technical assessment, which may include a take-home component or live coding
  • Depth in System Design

How to prepare

  • Answer aloud and timed: What are the primary considerations when designing APIs for high-availability systems?
  • Answer aloud and timed: How have you handled data privacy or compliance requirements (such as HIPAA) in your previous projects?

Technical Discussions

Deeper technical discussions with team members to evaluate technical fit.

What to demonstrate

  • Deeper technical discussions with team members to evaluate technical fit
  • Depth in System Design

How to prepare

  • Answer aloud and timed: What is your preferred approach to testing and ensuring code quality in a fast-paced environment?
  • Answer aloud and timed: Why do you want to work at Impiricus, and how does our mission resonate with your career goals?

Behavioral Leadership Interviews

Interviews focused on behavioral aspects to ensure cultural alignment with the team.

What to demonstrate

  • Interviews focused on behavioral aspects to ensure cultural alignment with the team
  • Depth in System Design

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

Where candidates lose points

Focus on the "Why

Don't just explain how you built something; explain why you chose that specific architecture or technology over the alternatives.

Know the Product

Research how Impiricus connects HCPs to pharma resources and be ready to discuss how your engineering work supports this mission.

Be Transparent

If you don't know an answer, be honest about it, but explain how you would go about finding the solution.

Prepare Questions

Have thoughtful, high-level questions ready for your interviewers, especially regarding engineering culture and technical strategy.

Questions & practice

How do you approach designing a system that needs to handle high concurrency?

Medium · Problem-Solving and Coding

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?

If given a feature request with ambiguous requirements, how do you proceed?

Medium · Problem-Solving and Coding

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?

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?

Explain why the owner filter ignores the listing index

Medium · composite index · query plans · sort elimination

The only index on resource is (tenant_id, status, updated_at DESC, resource_id DESC). A new endpoint returns one user's resources across all statuses, newest created first: WHERE tenant_id = $1 AND owner_user_id = $2 ORDER BY created_at DESC LIMIT 20. On a tenant with 2M rows it takes 900 ms and EXPLAIN shows a sort above a large scan. Explain precisely why the existing index cannot serve it, give the index that can, and state which of these the new index still will not help: owner_user_id alone across tenants; the same query ordered by updated_at. PostgreSQL 16.

Approach

  1. Separate the two jobs an index does. For filtering, a composite btree is seekable only on a left prefix, so with no predicate on status the scan can at best range over tenant_id and test owner_user_id per row; PostgreSQL 16 has no btree skip scan to jump the unconstrained column.
  2. For ordering, the index is sorted by (status, updated_at) within a tenant and not by created_at, so the LIMIT cannot stop early: every matching row is read and then sorted. That is the 'Sort Method: top-N heapsort' line, and it is why the plan reads 2M rows to answer with 20.
  3. Derive the replacement from the access path — equality, equality, then the ordering column: CREATE INDEX CONCURRENTLY ON resource (tenant_id, owner_user_id, created_at DESC). The scan seeks to the (tenant, owner) range and walks 20 entries in order, so the Sort node disappears along with the row-read.
  4. Treat INCLUDE (title, status) as conditional, not free. An index-only scan still visits the heap for any row whose page is not marked all-visible, so on a table taking 1.2k writes/second the win depends on autovacuum keeping the visibility map current, and the wider index costs more on every insert.

Follow-up

  • 90% of rows are status='active'. Would a partial index WHERE status = 'active' change your answer, and for which of the three queries?
  • A dashboard runs this for 40 owners in one page load. What changes about the design?

How do you approach building scalable, reliable backend services?

Medium · Technical and Domain Knowledge

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 primary considerations when designing APIs for high-availability systems?

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?

How have you handled data privacy or compliance requirements (such as HIPAA) in your previous projects?

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 preferred approach to testing and ensuring code quality in a fast-paced environment?

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?

How do you balance the need for speed with the necessity of building long-term, scalable architecture?

Medium · Behavioral and Leadership

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 critical production issue.

Medium · Problem-Solving and Coding

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 Impiricus candidates report.

Day 1 — Map the Impiricus loop

  • Write out the reported sequence: Recruiter Screen, Technical Assessment, Technical Discussions, Behavioral Leadership 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 System Design

  • Spend the session on System Design, which Impiricus candidates report being tested on.
  • Write one worked example in System Design and time yourself on it.

Deliverable: One timed worked example in System Design.

Day 3 — Work Backend Architecture

  • Spend the session on Backend Architecture, which Impiricus candidates report being tested on.
  • Write one worked example in Backend Architecture and time yourself on it.

Deliverable: One timed worked example in Backend Architecture.

Day 4 — Work Python

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

Deliverable: One timed worked example in Python.

Day 5 — Answer out loud: Technical and Domain Knowledge

  • Answer aloud, timed: How do you approach building scalable, reliable backend services?
  • Answer aloud, timed: Can you explain your experience with integrating LLMs or AI systems into a production environment?

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

Day 6 — Answer out loud: Behavioral and Leadership

  • Answer aloud, timed: Why do you want to work at Impiricus, and how does our mission resonate with your career goals?
  • Answer aloud, timed: Can you describe a time you had to resolve a technical disagreement within your team?

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

Day 7 — Answer out loud: Problem-Solving and Coding

  • Answer aloud, timed: Describe your process for debugging a critical production issue.
  • Answer aloud, timed: Walk me through a time you had to optimize a slow-performing query or service.

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

Behavioural preparation

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

Can you explain your experience with integrating LLMs or AI systems into a production environment?

Medium · Technical and Domain Knowledge

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?

Why do you want to work at Impiricus, and how does our mission resonate with your career goals?

Medium · Behavioral and Leadership

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 describe a time you had to resolve a technical disagreement within your team?

Medium · Behavioral and Leadership

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 us about a complex project you led from conception to production.

Medium · Behavioral and Leadership

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 feedback, and how do you provide it to others during code reviews?

Medium · Behavioral and Leadership

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?

Walk me through a time you had to optimize a slow-performing query or service.

Medium · Problem-Solving and Coding

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?