Principal Infrastructure Engineer / Tech Lead
Engineering · Posted 14 days ago
We need an experienced infrastructure engineer with 7+ years of experience who has led infrastructure projects and is comfortable building and scaling cloud systems (AWS preferred) in a fast-paced startup environment. You should have strong CS fundamentals, Python proficiency, and a track record of owning critical infr...
- Way of working
- On site
- Location
- San Francisco, CA
- Pay range
- $200,000 to $250,000
- Level
- Principal
- Experience
- 7+ years
- Type
- Full time
- Visa sponsorship
- Not offered for this role
- The company
- Software Development · under 20 people
Skills that matter here
What you would be doing
- Own and scale the cloud infrastructure (AWS) that powers custom AI model training and inference for enterprise customers
- Design and maintain reliable deployment processes, CI/CD pipelines, and infrastructure-as-code for getting models and services into production
- Manage GPU allocation, instance sizing, and cost optimization across cloud resources
- Build monitoring, logging, and automated testing infrastructure that gives the team visibility into what's running, failing, and why
- Own data and ML ops including ETL pipelines from varied customer data sources, model versioning, and lifecycle management
- Drive security engineering including data isolation between customers, infrastructure hardening, and SOC2 compliance
- Mentor and partner with the existing infrastructure engineer to raise the bar for the team
The full description
What we're looking for:
We need an experienced infrastructure engineer with 7+ years of experience who has led infrastructure projects and is comfortable building and scaling cloud systems (AWS preferred) in a fast-paced startup environment. You should have strong CS fundamentals, Python proficiency, and a track record of owning critical infrastructure end-to-end. Bonus points if you have familiarity with ML workflows or MLOps.
What you'll do:
- Own and scale the cloud infrastructure (AWS) that powers custom AI model training and inference for enterprise customers
- Design and maintain reliable deployment processes, CI/CD pipelines, and infrastructure-as-code for getting models and services into production
- Manage GPU allocation, instance sizing, and cost optimization across cloud resources
- Build monitoring, logging, and automated testing infrastructure that gives the team visibility into what's running, failing, and why
- Own data and ML ops including ETL pipelines from varied customer data sources, model versioning, and lifecycle management
- Drive security engineering including data isolation between customers, infrastructure hardening, and SOC2 compliance
- Mentor and partner with the existing infrastructure engineer to raise the bar for the team
How hiring runs
- 1Intro Call
- 2Coding Screen
- 3Take-Home Project
- 4Take-Home Presentation
- 5Final Onsite
Interested in this one?
There is no apply button here on purpose. Tell us about yourself, we book a short call, and if this role fits we walk you through the company and ask before anything is sent. Always free for you.
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