Careers
We work where the usual answers stop working.
Terabytes and up. Billions of rows. Telemetry with cardinality nobody planned for. At that scale the interesting question is never which framework — it is what the machine actually has to read, and how you make it read less. If that is the part of the job you like rather than tolerate, we should talk.
Open roles
Two, and both are foundational.
Solution Architect
Own the engagement end to end — from workload profiling and target architecture through integration, delivery, and client leadership. A hands-on player-coach role for someone who still wants to build.
Read the posting →Senior Data Engineer
Do the core engineering work: physical design, ingestion, query optimization, and performance tuning on analytical systems large enough that the decisions actually matter.
Read the posting →About Granule Labs
Granule Labs is an AI-native data engineering company focused on making organizational data usable by agents. We build the data layer that agents can actually use. An organization's data isn't ready for AI just because an agent can reach it. It has to answer at agent speed and volume, in real time, with meaning attached — at economics that still work as usage grows. Five conditions.
We do two things. We build high-performance data systems for AI and observability — real-time data at large scale, with the latency and economics required for heavy query workloads. We also leave clients stronger than we found them: senior engineers work alongside their teams, build repeatable tooling and patterns, and help them make the technical decisions that matter most.
We are standardizing on ClickHouse. Not out of loyalty — because of how it reads, how it stores, and how it performs. We are equally willing to say it is the wrong tool.
We are backed by Pure Play Partners and Gryphon Investors and led by operators who have built and delivered technology services businesses. We're in the early stages, and the people joining now will have an outsized role in defining how the company works.
How we work
Small senior teams, using AI as part of the engineering workflow, focused on problems where the technical and business value is large.
Four people. Twelve weeks. A result the client can measure.
We sell together, build together, and stay until it runs. The people who scope the work are accountable for delivering it, with few layers between the engineers doing the work and the client.
We do a small number of things, and we go deep on them. Every engagement starts from an offering rather than a blank page: reference architectures, workload profiling, and cost models ready to run on day one.
Clients pay for the answer, not for inventing the method.
What we look for in everyone
You have worked on genuinely large systems.
Not a large company — large data. You have seen query plans fail at scale, migrations run for days, and infrastructure decisions show up painfully on the bill.
You have made data fast for a real reason.
You diagnosed a workload, changed how the data was laid out, and watched the number move. Benchmarking someone else's dataset does not count.
You are genuinely interested in what AI changes.
Agent-driven workloads create different engineering problems, and the tooling is moving too quickly to stop learning.
You care about technical truth.
You want to understand why something worked, and you can tell a paying client, "this is the wrong tool," when that is the answer.
You are comfortable without a narrow lane.
This is an early company. You may move between architecture, engineering, client work, and building the practices the company itself needs.
We were raised in the Midwest, and we value substance over theater: do the work, know the details, and let the result speak for itself. The work is hard enough without pretending exhaustion is a credential.
Where we're probably wrong for you: if you want a narrowly defined role, highly predictable work, or a large organization around you, this will probably be uncomfortable. That's not a judgment — it's better for both of us to know now.
Location, compensation and benefits
Based in Minneapolis, MN or Seattle, WA. Some client travel, varying by engagement; not the majority of the job.
Base salary is listed on each role, plus eligibility for an annual performance bonus. Actual compensation depends on job-related skills, depth of experience, certifications, and location.
- Medical, dental, and vision coverage
- 401(k) with company contribution
- 4 weeks paid vacation + holidays
- AI and development tools, including Claude and OpenAI
- Annual budget for conferences, certifications, and hardware
- Client and employee referral bonuses
- Let us know what else is important to you
How we hire
We hire carefully, move quickly, and tell you where you stand.
If you meet most of the role, explain the gaps honestly and show us relevant work — a human will respond.
Four steps:
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Human phone screen
A real conversation about your work, not a checklist.
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Technical screen
A short assignment, live technical discussion, or coding exercise, depending on the role.
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Deep dive with the CTO
Architecture, tradeoffs, and the decisions you have had to defend.
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Final conversation with the CEO
How you work with clients, and whether this is the right place for you.
We aim to move quickly and tell you where you stand at every step.
If your experience doesn't line up exactly, apply anyway. We'd rather read your note than have you screen yourself out.
Visa sponsorship
We are not able to sponsor employment visas at this time. Applicants must be authorized to work in the United States without current or future sponsorship.
Equal employment opportunity
Granule Labs is an equal opportunity employer. We do not discriminate on the basis of age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical or mental ability, political affiliation, race, religion, sexual orientation, socioeconomic status, veteran status, or any other characteristic protected by applicable law.
We are committed to providing reasonable accommodations to applicants with disabilities. Contact careers@granulelabs.ai if you need an accommodation during the hiring process.
A note on recruiting fraud
All Granule Labs recruiting correspondence comes from an @granulelabs.ai address. We will never ask a candidate for payment, banking details, or government identification during the interview process.