Genmab · Software Engineer
Updated · 2026-10-02

Genmab Software Engineer
Interview Guide

THE 60-SECOND BRIEF

At Genmab, a Software Engineer—particularly those focused on CRM Platform Architecture, Software Development, or Enterprise AI/BI Analytics—serves as a critical bridge between cutting-edge biotechnology and the digital infrastructure that accelerates life-saving research. You are not just writing code; you are building the platforms that enable clinical data insights, streamline stakeholder engagement, and scale the computational power necessary for antibody discovery. This role requires a high degree of technical sophistication and a deep understanding of how software solutions impact scientific outcomes. Whether you are architecting a Veeva/Salesforce ecosystem or developing complex AI/BI analytics pipelines, your work directly influences the speed at which Genmab can deliver innovative therapies to patients.

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

No round sequence has been reported for Genmab. Confirm the format with your recruiter.

CRM Platform Architecture (Salesforce/Veeva)Enterprise AI PlatformBI Analytics Platform

21 min read

Browse Software Engineer questions

See the practice prompts

14Practice promptsAcross five skill areas

At Genmab, a Software Engineer—particularly those focused on CRM Platform Architecture, Software Development, or Enterprise AI/BI Analytics—serves as a critical bridge between cutting-edge biotechnology and the digital infrastructure that accelerates life-saving research. You are not just writing code; you are building the platforms that enable clinical data insights, streamline stakeholder engagement, and scale the computational power necessary for antibody discovery. This role requires a high degree of technical sophistication and a deep understanding of how software solutions impact scientific outcomes. Whether you are architecting a Veeva/Salesforce ecosystem or developing complex AI/BI analytics pipelines, your work directly influences the speed at which Genmab can deliver innovative therapies to patients. You will operate at the intersection of enterprise-grade software engineering and pharmaceutical operations, requiring both technical excellence and the ability to navigate complex, regulated environments. ##### Tip The roles at Genmab often require a blend of deep technical skill in specific platforms like Salesforce/Veeva and a strong understanding of how to translate business requirements into scalable, enterprise-grade architecture.

01

Preparation focus

editorial

No round sequence has been reported for this company, so confirm the format with your recruiter and work the reported questions below.

What to demonstrate

  • Breadth across the topics this company reports testing
  • Whether you confirm the format before preparing for it

How to prepare

  • Ask the recruiter for the sequence, the duration of each stage and whether you will be writing code
  • Work the reported questions below and time yourself
PracHub preparation framework ↗

PracHub editorial advice for the preparation topics above.

01

Understand the Business

Research Genmab’s current focus on antibody discovery and how digital platforms support that mission.

02

Structure Your Answers

Use the STAR (Situation, Task, Action, Result) method for behavioral questions to keep your responses concise and impactful.

03

Ask Strategic Questions

Use your interview time to ask about the team’s current technical challenges or the long-term vision for the platform you will be working on.

04

Focus on Scalability

Whether you are building a dashboard or a CRM module, always speak to how your solution handles growth and change over time.

Choose a category, try a prompt, then open its approach, worked solution or follow-up when you need it.

11 technical prompts0 include a worked solution

Archive a resource graph without breaking live references or recursing

medium
graph traversaltopological ordertenant 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?

Track a rolling failure rate per destination for circuit decisions

easy
sliding windowring buffercircuit 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?

Find overlapping job attempts and peak concurrency from lease records

medium
sweep lineintervalsleases

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?

Built from the topics and questions Genmab candidates report; no round sequence has been reported.

Small steps. Visible outcomes.0 / 7 completed
ONE WEEK · YOUR PACE

Prepare, practise & reflect

One practical outcome each day. Spend longer where you need it.

0 / 7 done
01Establish the Genmab format
  • No round sequence has been reported, so ask your recruiter for the sequence, the duration of each stage and whether you will write code.

Deliverable: A written reply from your recruiter confirming the format.

02Work CRM Platform Architecture (Salesforce/Veeva)
  • Spend the session on CRM Platform Architecture (Salesforce/Veeva), which Genmab candidates report being tested on.
  • Write one worked example in CRM Platform Architecture (Salesforce/Veeva) and time yourself on it.

Deliverable: One timed worked example in CRM Platform Architecture (Salesforce/Veeva).

03Work Enterprise AI Platform
  • Spend the session on Enterprise AI Platform, which Genmab candidates report being tested on.
  • Write one worked example in Enterprise AI Platform and time yourself on it.

Deliverable: One timed worked example in Enterprise AI Platform.

04Work BI Analytics Platform
  • Spend the session on BI Analytics Platform, which Genmab candidates report being tested on.
  • Write one worked example in BI Analytics Platform and time yourself on it.

Deliverable: One timed worked example in BI Analytics Platform.

05Answer out loud: Technical & Platform Expertise
  • Answer aloud, timed: These questions evaluate your hands-on experience with specific stacks like Salesforce/Veeva or AI/BI tools.
  • Answer aloud, timed: How do you approach integrating disparate data sources into a centralized CRM or Analytics platform?

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

06Rehearse your own examples
  • Prepare three examples from your own work where you made the decision, each with the outcome you can quantify.

Deliverable: Three examples written out, each with a number attached.

07Dry run for Genmab
  • Run one full mock under time, then write down the two questions you most want to ask your interviewers.

Deliverable: A completed timed mock and two questions to ask.

Expand any day for tasks and deliverables. Your progress is saved on this device.

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

Describe a time you had to optimize a complex database query or a slow-performing system integration.

medium
Technical & Platform Expertise

Describe a time you had to optimize a complex database query or a slow-performing system integration.

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 callers you do not own that their integration breaks

medium
deprecationcompatibilitystakeholders

A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.

Approach
  1. Establish the reader set empirically rather than from a wiki of owners: per-field usage counters keyed by principal, or access logs attributed to a consumer. State the blind spot of whichever you pick, since a consumer that reads the field only on a monthly job will not appear in a week of logs.
  2. Ship additive first. Populate the new field alongside the old one so no reader is forced to move, which is also what keeps a rolling deploy safe, because old and new instances answer the same requests at the same time and a rollback must still find the old shape present.
  3. Set the window from the slowest legitimate consumer's release cadence, not from your calendar, and decide separately what to do for a consumer with no release process at all, such as an external webhook endpoint you can only email.
  4. Convert silence into evidence before you rely on it: a short, low-traffic removal window that makes a still-dependent consumer fail visibly and loudly while you are watching, rather than at three in the morning after you have moved on.
Follow-up
  • How would you detect a consumer that reads the field only during a monthly export?
  • One caller refuses to move and has a commercial relationship behind it. What changes in your plan and what does not?

Unblock an engineer without taking the keyboard

easy
mentoringleasesat-least-once

A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.

Approach
  1. Ask before diagnosing, and ask for things answerable from data they already have: the attempt count on the job rows that produced duplicates, the handler's observed duration against its lease expiry, and whether the duplicate rows share a natural key that a unique constraint could have caught.
  2. Teach the shape rather than the answer. A lease cannot distinguish a dead worker from a slow one, so a handler that outruns its lease is running twice by design, and deploys deliver the other half by killing handlers mid-run on every rollout. Both of their candidate theories produce identical duplicate rows, which is why the evidence has to come from timings rather than from argument.
  3. Hand over a checklist they execute: a natural key on every write the handler performs so the second copy collides rather than appends, the record of intent written before any external effect, a lease heartbeat while running, and the metric that shows it working.
  4. Keep ownership with them deliberately. Pair on the first write, then step back; if you finish it yourself you have closed one ticket and left the same person stuck on the next redelivery.
Follow-up
  • How would you distinguish a genuine double-delivery from a lease expiry using only the data already stored?
  • Their handler calls an external endpoint before recording that it did. What do you tell them to change first?
  • 01

    Describe a time you had to optimize a complex database query or a slow-performing system integration.

  • 02

    A field in a write endpoint's response must change shape. You own the endpoint; you do not own the four internal callers or the outbound webhook consumers who read it. Describe a deprecation you were responsible for: what you shipped first, how you established who was actually reading the field, the window you gave and what set its length, what you did about the consumer who never moved, and how you decided removal was safe. Name the signal you used, not the announcement you sent.

  • 03

    A teammate has spent two days on a job handler that occasionally writes duplicate rows. They are certain the queue is delivering twice by mistake. You suspect a lease expiring under a slow handler, so the job is running concurrently with itself. Describe how you have unblocked someone in this position: what you asked before offering a hypothesis, what you showed them rather than told them, and what you left them owning. Then say what you would do if their theory turned out to be the right one.

PracHub preparation framework ↗
How long does the interview process typically take?

While it varies by role and team, most candidates complete the process within 4–6 weeks. We prioritize quality over speed to ensure the best fit for both you and the team.

Genmab Software Engineer candidate reports ↗
What differentiates a successful candidate at Genmab?

Beyond technical skill, we look for "intellectual curiosity" and "collaborative spirit." Successful candidates are those who ask insightful questions about how their work impacts the broader business and patient outcomes.

Genmab Software Engineer candidate reports ↗
Is there a specific coding language I should focus on?

While we use various languages, focus on demonstrating mastery of the languages relevant to your specific domain (e.g., Apex for Salesforce, Python for AI/BI). We value candidates who can pick up new tools quickly.

Genmab Software Engineer candidate reports ↗
How much remote work is expected?

Genmab values the energy of in-person collaboration, particularly for roles based in Princeton, NJ. Expect a hybrid working model that balances focused independent work with team-based collaboration.

Genmab Software Engineer candidate reports ↗
What topics does Genmab test in interviews?

Genmab interviews most often cover Cross-functional Collaboration, Project Management, Product Management, Data Engineering (core responsibilities), and Oncology (Therapeutic Area). The exact emphasis depends on the specific role you apply for.

Genmab Software Engineer candidate reports ↗
Sources & methodology 3 sources ↗

No official company page is cited. Rounds and questions come from candidate reports and PracHub editorial material; each source shows the date it was read.