Senior Infrastructure Engineer (AI Data & Cloud Systems)
Build foundational AI infrastructure by designing secure, scalable cloud and data systems for a fast-growing AI company. Own end-to-end solutions for multi-cloud deployments, real-time data pipelines, and AI-ready data normalization. Join an early-stage team shaping critical infrastructure for financial institutions.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
INFRASTRUCTURE ENGINEER
Build the systems AI actually depends on.
Most AI products get all the attention at the model layer.
The harder problem is underneath it.
How do you securely turn decades of messy, proprietary enterprise data into something AI can actually use — without losing context, trust, or control?
That’s the problem this team is solving.
They’re a fast-growing Series A AI company working with sophisticated financial institutions, and demand is already moving faster than the engineering team can support.
They need more builders.
WHAT YOU’LL BUILD
This role can lean one of two ways:
Cloud Infrastructure
Build and scale secure deployments across AWS, GCP, and Azure. Think Kubernetes, private cloud / BYOC, observability, infrastructure-as-code, security, and multi-cloud orchestration.
Data Infrastructure
Build the systems that ingest and normalize large volumes of structured and unstructured data — and make it usable by AI in real time.
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Either way, this is not a keep-the-lights-on infrastructure job.
You’ll be building foundational systems from the ground up.
YOU’LL PROBABLY LIKE THIS IF...
You’ve worked somewhere where the engineering bar was legitimately high.
You’ve owned systems instead of just contributing tickets.
You care about infrastructure because the product fails without it.
You want an early-stage environment with real ownership and ambiguity.
And you want the thing you’re building to solve meaningful, difficult problems — not just become another SaaS dashboard.
THE SIGNAL WE CARE ABOUT
We’re less interested in checking every technology box than seeing evidence that you can operate at a very high level.
- Strong signals include:Deep AWS, GCP, or Azure experience
- Kubernetes / containers at meaningful scale
- Cloud platform or data infrastructure ownership
- Complex ingestion / real-time data systems
- Security-first architecture
- ML / AI infrastructure exposure
- Early-stage or 0→1 experience
- Fast career progression and expanding scope
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Experience in demanding, high-ownership engineering environments will stand out.
We care more about the bar you operated at and what you personally built than matching a perfect logo list.
WHY THIS ONE IS DIFFERENT
The company is still early.
But the market demand is real.
Customers are showing up faster than the current engineering team can support them.
So the opportunity here isn’t:
Join and optimize something that’s already finished.
It’s:
Help decide how the foundation gets built.
If you’re wired for that kind of work, we’d love to talk.
$150K–$300K base + equity
San Francisco or New York City — onsite
Visa sponsorship / transfers available
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