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Infrastructure Software Engineer, Enterprise GenAI

On-site
Scale AISan Francisco, CA, US / New York, NY, US6 months agoWebsite
May be filled
Enterprise Engineering

Compensation

$216,000-$270,000/yr
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Description

Scale GP (Scale Generative AI Platform) is an enterprise-grade AI platform that provides APIs for knowledge retrieval, inference, evaluation, and more. We are looking for a strong engineer to join our team and help us build and scale our core infrastructure in a fast-paced environment. 

The ideal candidate will have a strong understanding of software engineering principles and practices, as well as experience with large-scale distributed systems. You will implement solutions across multiple cloud providers (GCP, Azure, AWS) for customers in diverse, highly-regulated industries like healthcare, telecom, finance, and retail.

What You’ll Do:

  • Architect multi-cloud systems and abstractions to allow the SGP platform to run on top of existing Cloud providers
  • Implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs)
  • Collaborate with platform, product teams and our customers directly to develop and implement innovative infrastructure that scales to meet evolving needs.
  • Deliver experiments at a high velocity and level of quality to engage our customers
  • Work across the entire product lifecycle from conceptualization through production
  • Be able, and willing, to multi-task and learn new technologies quickly

What We’re Looking For:

  • 4+ years of full-time engineering experience, post-graduation
  • Experience scaling products at hyper growth startups
  • Experience tinkering with or productizing LLMs, vector databases, and the other latest AI technologies
  • Proficient in Python or Javascript/Typescript, and SQL
  • Experience with Kubernetes
  • Experience with major cloud providers (AWS, Azure, GCP)
  • Excellent communication skills with the ability to explain technical concepts to both technical and non-technical audiences

Stack

LLMsGenerative AIPythonGCPAzureTypeScriptJavaScriptSQLVector DatabasesDistributed SystemsAWSKubernetes
Posted
Feb 24, 2026
Last seen
Jul 2, 2026
First seen
Jun 25, 2026

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