We're genuinely excited you're considering joining us. HiveMQ is at a defining moment — building the industrial data platform that powers Agentic AI for the world's most critical operations.
This guide will help you understand our process, our expectations, and how to put your best foot forward.
About us
Who we are
HiveMQ is The Industrial Data Platform for Agentic AI. Built on MQTT, we connect, contextualize, analyze, and enable action on real-time operational data — powering trusted, AI-ready pipelines that deliver measurable outcomes for the world's most demanding enterprises.
Founded in Germany in 2012, we are a fully remote-first company with around 150 people across Europe and the United States. Our US presence is a significant and growing part of the business, with team members spanning commercial, engineering, product, and go-to-market functions.
~150
People globally, remote-first
140B
Data points streamed per day (FPL)
99.999%
Reliability for mission-critical ops
Our platform moves customers through three stages:
Data Streaming — connecting assets reliably at scale with MQTT
Data Intelligence — contextualizing, governing, and analyzing that data
Agentic AI — enabling autonomous, real-time decision-making at the edge
This isn't a roadmap aspiration — it's the journey our customers are on today.
Vision: Unlock value at the intersection of the physical world and AI.
Mission: Help customers progress from AI-ready data streaming, to real-time data intelligence, to autonomous actions at the edge.
Values
Our values aren't a wall poster — they shape how we hire, how we work, and what we reward. Here's what we're listening for in your answers:
⚡Effortless
We make the complex simple
We look for people who naturally seek to simplify, automate, and remove friction — who instinctively ask "how do we make this easier?" rather than tolerating unnecessary complexity.
AutomateStreamlineSimplifyRemove friction
🙌Empowered
We trust our people
We look for people who take initiative, make decisions independently, and feel genuine ownership over their outcomes.
OwnershipAutonomyInitiativeAccountability
🚀Relentless
We never settle
We look for people who push for meaningful, lasting improvement — not just quick fixes. People who care deeply about quality, long-term impact, and raising the bar continuously.
DriveContinuous improvementNever settleTenacious
⚡ Effortless — our product is exceptional, intuitive, and instantly adopted. Our people make the complex feel simple.
🙌 Empowered — our people are trusted, accountable, and customer-obsessed. They make decisions and own outcomes.
🚀 Relentless — our performance is world-class, innovative, and AI-driven. We never stop improving.
Industries we serve
HiveMQ operates at the intersection of industrial operations and modern data infrastructure. Our platform is trusted across sectors where real-time data reliability is mission-critical.
Our customers — and the problems we solve for them
Our customers operate in environments where data loss, latency, or downtime carry serious real-world consequences. Enterprises like Audi, BMW, Ford, Mercedes-Benz, Siemens, Liberty Global, and Eli Lilly choose HiveMQ because reliability is non-negotiable for them.
Before your interviews, we encourage you to explore the platform, read a few case studies, and form a genuine point of view on the problem space. Candidates who understand what MQTT is, why it's irreplaceable in industrial environments, and where HiveMQ sits in the journey from streaming to agentic AI consistently stand out.
The experience
What to expect from our process
Our interview process is designed to be transparent, efficient, and genuinely two-directional. Every stage is an opportunity for both sides to learn — we want to understand how you work, what drives you, and whether HiveMQ is the right environment for you to do your best work. We want you to walk away with a clear picture of us, too.
One thing we care about: we want to hear about you. When discussing team achievements, tell us what you personally owned, decided, and drove. We're interested in your judgment, your initiative, and your impact — not just the team's collective output.
Throughout the process, expect a blend of behavioural, situational, and technical questions. The right framework to prepare with is the STAR method. Your answers should be specific, grounded in real examples, and honest — including about failures and what you learned from them.
We use Metaview, an AI note-taking assistant, during interviews so our interviewers can stay fully focused on the conversation rather than taking notes. You'll see it in the Zoom call. If you'd prefer not to have it present, just let your recruiter know before the interview — you can opt out at any time, no questions asked.
The process
Our recruitment process
Our process typically runs up to six stages, though the exact path and timelines may vary depending on the role and team. Each stage is designed to give both sides a genuine opportunity to connect, explore fit, and make a well-informed decision. Here's what each one involves and how to make the most of it.
📋
Application
→
📞
Recruiter Screening
→
🤝
Hiring Manager Interview
→
📝
THA / Case Study / Demo
→
🔍
Deep Dive Interview
→
⭐
Final Interview
1
Application
Your starting point
Submit your application via our careers page. Please ensure your CV is in English and in a clear, professional format (PDF preferred). It should accurately reflect your experience and — where possible — the measurable impact you've had in past roles.
2
30–45 minutes · Recruiter Screening
Meeting your recruiter
This is a two-way conversation. Your recruiter will share more about HiveMQ, the role, and the team. They'll explore your background, motivations, and career goals — and you'll have time to ask your own questions. Compensation expectations are discussed here so there are no surprises later in the process.
How to prepare: Review the job description closely. Prepare a concise summary of your background and what draws you to HiveMQ specifically. Have 2–3 genuine questions ready about the role, the team, or HiveMQ's culture.
3
30–60 minutes · Hiring Manager Interview
Meeting your potential manager
This is your first conversation with the person you'd report to. Expect a deeper exploration of your experience, how you approach problems, and how you operate as part of a team. The focus is on role fit, culture, and mutual exploration of the opportunity. You'll also have the chance to ask specific questions about the team's goals, projects, and day-to-day realities.
How to prepare: Use the STAR method. Think about 3–5 concrete examples from your work that demonstrate relevant skills and personal ownership. Prepare questions about what success looks like in this role after 30, 60, and 90 days.
4
3–5 working days · Take-home assignment or demo preparation
Showing your thinking before the room
Depending on the role, you'll be asked to complete a take-home task or prepare a case study, demo, or presentation ahead of the deep dive. This stage is about how you work — not just what you produce.
For technical roles, you'll receive a practical task that reflects challenges you'd encounter in the role, with approximately 3–5 working days to complete it. For GTM, G&A, and other non-technical roles, you'll typically prepare a case study, strategy presentation, or demo that you'll present live during the next stage.
On using AI tools: You're welcome to use AI assistance during any take-home task. What we're evaluating is your judgment — be prepared to explain every decision, defend your approach, and demonstrate that you fully own the solution you submit.
How to prepare: Read all task materials carefully before you start. If anything is unclear, reach out to your recruiter as early as possible. Think about your process, not just your output. Innovation in format and approach is always welcome.
5
60–120 minutes · Deep Dive Interview
Presenting your work and meeting the team
Here you'll present your task, demo, or case study and walk the team through your thinking. There will be a Q&A from the interviewers, followed by time for you to ask questions of the people you'd work with daily.
For technical roles, this dives deeper into your technical depth — expect questions that go beyond the task, including architecture, trade-offs, and how you'd approach problems you haven't seen before.
How to prepare: Revisit your submission and be ready to explain every choice you made. We're as interested in where you struggled and what you'd do differently as we are in what you got right. Show us how you think, not just what you built.
6
30–60 minutes · Final Interview
Values, strategy, and alignment
The final conversation is with a senior leader or member of our executive team. This is less a test and more a discussion — about where HiveMQ is heading, how you see yourself contributing, and whether there's a genuine alignment in values and ambition. Come with big questions. We love candidates who think about the long game.
How to prepare: Reflect on HiveMQ's vision and mission. Think about how your work connects to where the company is going. Prepare questions about strategy, direction, and the kind of company we're building together.
Framework
The STAR method
We ask behavioural and situational questions throughout the process. The STAR method gives your answers structure and makes them easy to follow. Use it as a guide — not a rigid script.
S
Situation
Set the context. What was the challenge or environment you were operating in?
T
Task
What was your specific role or responsibility in that situation?
A
Action
What did you personally do? Be specific about your decisions and contributions.
R
Result
What happened? Quantify the impact where possible — and include what you learned.
One thing to remember: we value the full picture — including failures. Candidates who speak clearly about what went wrong, what they'd do differently, and what they learned from it stand out. Intellectual honesty is something we look for and deeply respect.
Common pitfalls
Why candidates don't move forward — and how to avoid it
We share these patterns because we genuinely want you to succeed. The examples below are illustrative — they show the kind of thinking that lands well versus what falls short. We fully expect you to bring your own original answers grounded in your real experiences and your own story.
Vague or generic motivation for joining
What works instead: Be specific about why HiveMQ, why this role, and why now. Reference something real — a customer story, our platform vision, a product decision you found interesting. Generic enthusiasm doesn't differentiate you.
Answers lack specificity or measurable impact
What works instead: Use the STAR method with real numbers and outcomes from your own work. Vague claims tell us very little. Specific examples with clear results — from your actual experience — tell us a great deal.
Not researching HiveMQ
What works instead: Understand what HiveMQ is doing and why it matters for our enterprise customers. You don't need to be an expert — but showing curiosity and preparation signals a lot.
Talking about "we" instead of "I"
What works instead: We want to understand your individual contribution. Own your impact clearly — tell us what you specifically did, decided, or drove.
Not asking questions
What works instead: Interviews are two-way. Thoughtful questions about the team, product direction, or challenges signal genuine interest and strategic thinking. "No questions" is a missed opportunity.
Practical advice
Tips for a successful interview at HiveMQ
Before the interview
Explore the HiveMQ website, read at least one case study, and understand what MQTT is and why it's irreplaceable in industrial environments.
Re-read the job description and identify the 3–5 skills most central to the role. Prepare concrete, original examples from your own background for each.
Structure 3–5 STAR-based stories from your real work that demonstrate impact, ownership, and growth.
Prepare 2–4 thoughtful questions you genuinely want answered — about the team, the product roadmap, the strategy, or HiveMQ's culture.
During the interview
Think aloud. We want to understand how you approach problems — your reasoning matters as much as your conclusion.
Be direct and confident. We're a direct team. Say what you think — you don't need to hedge everything.
Be honest about what you don't know. "I'm not certain, but here's how I'd approach finding out" is a strong answer.
Look at the camera, not your screen. It makes a genuine difference in remote conversations.
Manage your time. If a question is broad, take a moment to structure your answer before diving in.
On remote setup
We interview on Zoom — make sure you're set up and tested well in advance.
Audio quality matters more than a polished background. Test your microphone beforehand.
Sit facing natural light or a lamp — good lighting makes a real difference on camera.
Minimize distractions: close extra tabs, silence notifications, and give yourself space to focus.
Benchmarks
What good looks like
Here's how we distinguish strong candidates across the dimensions that matter most.
✓ Strong signals
Specific examples with measurable results
Clear ownership of decisions and outcomes
Genuine curiosity about HiveMQ's technology
Thoughtful questions that show strategic thinking
Self-aware about strengths and growth areas
Concise, structured communication
✗ Weak signals
Generic, rehearsed-sounding answers
"We did this" without personal accountability
No research on HiveMQ or the problem space
No questions for the interviewer
Answers that lack detail or measurable impact
Overselling without substance to back it up
Preparation
Resources to help you prepare
These are the best places to learn more about HiveMQ before your interviews.
Interviewing takes time and energy. We respect that. Our aim is to make every stage of this process feel worthwhile — regardless of the outcome.
The candidates who do best here aren't the ones with the most polished answers. They're the ones who show up genuinely prepared, intellectually honest, and authentically excited about what we're building. They ask real questions. They're specific. They own their story.
We hope that's you. Good luck — we look forward to the conversation.
