Humana software engineer candidates commonly report a recorded video screen, a behavioral conversation, and a resume-driven technical discussion, usually with little or no live coding.
$113K
Avg. Base Comp
$139K
Avg. Total Comp
2-4 rounds
Typical Rounds
Not reported
Process Length
Candidates who interviewed for Humana software roles mostly describe a resume-driven process rather than an algorithm grind. Several started with an asynchronous video screen with questions about why Humana, relevant background, and what they were doing to build professional skills. A behavioral round followed, with prompts such as conflict with a coworker and prioritizing when everything feels urgent. One candidate was also asked how they approach using AI tools like ChatGPT.
The technical stage was usually conversational. Candidates for software engineer and related roles say they were asked to walk through projects and explain technical decisions. Some were asked about concepts tied to their resume, such as arrays versus linked lists, trees, or RESTful APIs in .NET Core. Several said there was no live coding, but because conceptual data structure questions did come up, a light refresher is sensible.
Expect some interviews with several panelists on the call, and expect questions about fit and motivation, including why Humana. Outcomes were mixed: some candidates received offers, and others heard nothing or received a late automated rejection. Communication from recruiting frustrated some candidates, so confirm next steps at the end of each stage. Prepare two or three project stories with your role, trade-offs, and results, and have specific reasons for choosing Humana.
Synthesized from 11 candidate reports by our editorial team.
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Real interview reports from people who went through the Humana process.
I started with an asynchronous recorded interview—no video chat, just an intro, then my pre-recorded answers to questions. A day later I got the invite to a panel with three people. I was honestly braced for something formal, but it ended up being really conversational and low-pressure. They asked about my recent experience, why I wanted to leave my current job, and what I knew about the company. No SAR framework, no competency-based questioning, just a genuine chat about fit. The whole thing felt unstructured in a good way—they were clearly interested in whether I'd work well with the team rather than whether I could recite textbook answers. I talked to people from different levels, some inside the team and some outside, which gave me a real sense of who I'd be working with. The pace was fast and friendly; the whole process felt efficient without being cold. They also mentioned upfront that drug testing and background checks would be part of the final stage, so no surprises there.
Prep tip from this candidate
Prepare to talk genuinely about your experience and why you're moving, but skip memorizing behavioral frameworks—this interview values authenticity over polish. Know enough about the company to show interest, but they're far more focused on team fit than grilling you on the job description.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
| Question | |
|---|---|
| P-value to a Layman | |
| Always Excited Users | |
| Hurdles In Data Projects | |
| Common Prefix | |
| Count Transactions | |
| Integer String Addition | |
| Moving Window | |
| Sports App Cheater | |
| Your Strengths and Weaknesses | |
| Top Three Salaries | |
| Comments Histogram | |
| Bagging vs Boosting | |
| Data Pipelines and Aggregation | |
| Ride-Sharing App Schema | |
| Swap Variables | |
| International e-Commerce Warehouse | |
| Distributed Authentication Model | |
| Why Do You Want to Work With Us | |
| Decision Tree Evaluation | |
| Payment Data Pipeline | |
| Stakeholder Communication | |
| Friend Requests Down | |
| Presentations and Insights | |
| Game Feature Home | |
| Unstructured Data Pipeline (ETL) | |
| Best DAU | |
| Bootstrapping Samples | |
| Choosing Between Python and SQL | |
| 2nd Highest Salary |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report starting with a HireVue-style or self-recorded video screen with a few pre-set questions. Topics included why Humana, background, and what you are doing to build professional skills. It was typically behavioral rather than technical, and some candidates mention multiple attempts per answer.
Several candidates describe a live behavioral round of roughly 30 to 45 minutes. Reported prompts include handling conflict, balancing or prioritizing competing work, and describing past situations. Candidates generally describe a relaxed, conversational tone, so prepare concise STAR-style stories.
Most candidates describe the technical round as a conversation about their resume. They were asked to explain projects, technical decisions, and concepts such as data structures or REST APIs. Several report no live coding or LeetCode-style problems.
Some candidates report a panel of three or four people or a final talk with a leader or hiring manager, focused on experience, motivation, and team fit. One candidate says drug testing and a background check were mentioned for the final stage. Timelines and follow-up reportedly varied, so ask about next steps.
