Senior Infrastructure Engineer (AI Data & Cloud Systems)

Talanto

San Francisco, Northern (CA, KY)

Hybrid

USD 58,000 - 87,000

Full time

14 days+
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Job summary

Talanto is seeking an Infrastructure Engineer in San Francisco to build secure, scalable deployments across AWS, GCP and Azure, with Kubernetes, observability, IaC and multi‑cloud orchestration at the core. You’ll design and own data infrastructure that ingests and normalizes large volumes of structured and unstructured data in real time, enabling AI products to operate with trust and context.

We value engineers who have owned complex systems in early‑stage settings and can drive foundation

Qualifications

  • Deep cloud experience across AWS, GCP, or Azure.
  • Kubernetes or containers at meaningful scale.
  • Cloud platform or data infrastructure ownership.
  • Early-stage or 0→1 experience.
  • Fast career progression and expanding scope.

Responsibilities

  • Build and scale secure deployments across AWS, GCP, and Azure with Kubernetes and IaC.
  • Own data infrastructure to ingest and normalize large volumes of data in real time.
  • Drive foundational systems from the ground up in an early-stage environment.

Skills

AWS
GCP
Azure
Kubernetes
Multi-cloud
Observability
Infrastructure as Code
Data infrastructure ownership

Job description

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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:

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.

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
  • Early-stage or 0→1 experience
  • Fast career progression and expanding scope

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.

4842–7263 $

The range shows the lower and upper market bands: 25% of vacancies pay below the first value, the median is the typical salary, and 75% marks the upper band.

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