Cloud/Python Engineer (AI PLATFORM, San Francisco Bay Area) 4 days onsite

If you have built and operated cloud infrastructure at scale, write production Python seriously, and want to own the infrastructure decisions at an early-stage AI company rather than inherit someone else's, this is worth a read.

The role

You would join as the second engineer on the cloud infrastructure team, reporting directly to the VP of Engineering. The broader engineering team is around 20 people with a flat structure. This is an early hire with real ownership: you are not walking into a defined platform with established patterns. You are helping to build them.

Why it's worth a look

The infrastructure problem here is genuinely complex. You are architecting multi-cloud systems, AWS primary, across GCP, Azure, OCI and on-prem, supporting enterprise customers running large-scale ML training and data processing workloads. The team is small enough that the choices you make matter and the scope is wide enough that you will not be siloed. The compensation reflects that seriousness: $200K to $300K base plus meaningful equity. The company is at an inflection point, growing a customer pipeline and scaling the team, so the timing is good for someone who wants to grow with it.

What you'll be doing

- Architect and maintain multi-cloud infrastructure across AWS (primary), GCP, Azure, OCI and on-prem to support enterprise customer deployments

- Define and implement infrastructure-as-code using Terraform or Pulumi, setting best practices for the team

- Design and manage Kubernetes-based systems for ML model training, inference and data processing workloads

- Write production-quality Python daily, building real systems rather than scripts

- Optimise CI/CD pipelines and streamline service deployment across customer environments

- Build monitoring, alerting and logging systems to maintain high availability and observability

- Collaborate with research and engineering teams to support large-scale ML training infrastructure

- Drive cost-efficiency across compute and storage resources

- Respond to and resolve infrastructure incidents with ownership

What they're looking for

Must have:

- 4 or more years of hands-on cloud infrastructure engineering experience at production scale

- Strong Python coding ability, tested rigorously in the interview process, not scripting-only

- Solid AWS experience, hands-on and production-grade

- Kubernetes and containerised architecture expertise in production environments

- Infrastructure-as-code experience

- Experience designing and operating highly available, scalable infrastructure systems

- CI/CD pipelines, monitoring, observability and systems-level debugging

- BS in Computer Science, Electrical Engineering or a related engineering discipline

- Comfortable working in a small, high-ownership team with limited process overhead

Nice to have:

- Multi-cloud experience beyond AWS: GCP, Azure, OCI or on-prem deployments

- Go or Bash scripting in addition to Python

- Experience supporting ML training or inference workloads

- Background in platform engineering or developer tooling

- Familiarity with Helm, Docker, CloudFormation or similar tooling

Package

- Base salary $200,000 to $300,000 depending on experience

- Meaningful equity

- Hybrid, 4 days per week Relocation assistance available

- Visa sponsorship available

- Comprehensive health cover, retirement contribution, generous PTO

- Wellness and learning and development budget, plus additional day-to-day perks

If the scope and stage of this feels like the right fit, get in touch with Daryl Crothers at Oxbow Talent to find out more.

Oxbow Talent

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