Senior Infrastructure Engineer – Multi-Cloud Data Platform

DatologyAI; California; On-site; USD 180,000 - 300,000; Full time

Benefits offered by this job

Health benefits

4% 401(k) company match

Unlimited PTO

Parental Leave 12 weeks + 6 months WFH

Wellness stipend

Learning & development stipend

Lunches and snacks provided

Relocation assistance

Job summary

DatologyAI is seeking an experienced Infrastructure Engineer to join our core team in San Mateo, CA. You will lead development of our data infrastructure, support multi-cloud deployment models, and shape the direction of our production and training environments.

You will collaborate with researchers and engineers to bring new capabilities to customers, own end-to-end problems, and drive reliability, security, and performance at scale across platforms.

Qualifications

• 4+ years of relevant infrastructure experience.
• Experience building large-scale infrastructure.
• Proficiency in Bash, Kubernetes, Python, and Terraform.
• Experience with AWS, Azure or GCP and/or on-prem.
• Ability to debug networking, performance, or memory issues.
• Own problems end-to-end and collaborate well.

Responsibilities

• Design and build the development and production platforms that power our products, enabling reliability and security at scale
• Architect, build, and deploy our core infrastructure while supporting multiple cloud providers and various deployment models
• Accelerate company productivity by empowering your fellow engineers & teammates with excellent tooling and systems, providing a best-in-case experience
• Partner with researchers and engineers to bring new features and research capabilities to our customers

Skills

Infrastructure ownership

End-to-end ownership

Debugging across stack

Team collaboration

Tools

Kubernetes

Python

Terraform

Bash

AWS

Azure

GCP

Job description

DatologyAI is seeking an experienced Infrastructure Engineer to join our core team in San Mateo, CA. You will lead development of our data infrastructure, support multi-cloud deployment models, and shape the direction of our production and training environments.

You will collaborate with researchers and engineers to bring new capabilities to customers, own end-to-end problems, and drive reliability, security, and performance at scale across platforms.