Infrastructure Engineer – AI / Cloud Infrastructure

Location: San Francisco, CA (Onsite)

Compensation: $150,000–$300,000 base + Equity

Employment: Full-time

I'm partnering with a well-funded AI startup building sophisticated data infrastructure for some of the world's leading investment firms. Backed by $50M from top-tier investors, the company is developing an enterprise AI platform that enables financial institutions to securely leverage proprietary data and make better investment decisions.

They're looking for an experienced Infrastructure Engineer to help architect, build and scale the underlying platform, working on challenging problems across cloud infrastructure, distributed systems, data security and AI workloads.

What you'll be doing

Designing and scaling cloud infrastructure supporting enterprise AI applications and large-scale financial datasets.
Building secure, multi-tenant systems with strict data isolation, access controls and governance.
Developing infrastructure for data ingestion, processing and integration across structured and unstructured sources.
Supporting LLM inference, AI agents and machine learning workloads.
Implementing Kubernetes, infrastructure-as-code and CI/CD pipelines across cloud environments.
Building monitoring, observability and reliability systems for production infrastructure.
Collaborating closely with engineering, AI research and product teams.

What we're looking for

5+ years of experience in Infrastructure Engineering, Platform Engineering or a similar role.
Strong experience with AWS, GCP or Azure.
Hands-on expertise with Kubernetes, containers and infrastructure automation.
Experience building scalable, reliable distributed systems.
Strong understanding of cloud security, access management and data protection.
Familiarity with observability tools such as Datadog.
Experience in high-growth startups or fast-paced engineering environments.

Nice to have

Experience supporting AI/ML infrastructure, LLMs or AI agents.
Exposure to regulated environments, particularly financial services.
Experience with private cloud deployments or bring-your-own-cloud architectures.

Why consider it?

An opportunity to join an ambitious, heavily funded AI startup at an early stage, take significant ownership of core infrastructure decisions and work on technically demanding problems at the intersection of AI, cloud engineering and financial technology.

Radley James

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