Founding Platform Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Founding Platform Engineer (AI): Building the foundational compute, orchestration, and infrastructure layer for a Gen AI-driven code review platform with an accent on Kubernetes internals, multi-region GCP architecture, and high-scale distributed systems. Focus on establishing technical direction from 0-to-1, designing robust automation patterns, and ensuring system reliability for a rapidly growing product suite.
Location: Must be based in or able to work from San Francisco (Hybrid)
Salary: $220,000 – $280,000
Company
is an innovative R&D company building AI-native developer tooling that creates a symbiotic partnership between humans and advanced algorithms for code review.
What you will do
- Design and own the compute, orchestration, and infrastructure layer for the AI engine.
- Establish technical direction and architectural patterns for the platform from the ground up.
- Manage a multi-region GCP footprint with a focus on scalability and reliability.
- Build platform tooling and automation using Go or Node.js/TypeScript.
- Implement advanced infrastructure as code using Terraform.
- Ensure high standards for observability, monitoring, and alerting across the platform.
Requirements
- 7+ years of experience in Platform, Infrastructure, or Site Reliability Engineering.
- Deep hands-on experience with Kubernetes internals, including operators, controllers, and runtime debugging.
- Strong background in GCP or AWS, focusing on infrastructure primitives rather than managed services.
- Experience building and running large-scale distributed systems in production.
- Proficiency in Docker and container runtime internals.
- Ability to work in a high-ownership, fast-paced startup environment.
Culture & Benefits
- High-ownership engineering culture with a bias toward action and shipping.
- Opportunity to build foundational tools that change how software is written.
- Competitive compensation package including equity.
- Collaborative environment prioritizing collective intelligence and rapid learning.
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