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HomeCompaniesScale AIInfrastructure Software Engineer, Enterprise GenAI

Infrastructure Software Engineer, Enterprise GenAI

Scale AI · San Francisco, CA; New York, NY · Active · $216,000–$270,000 / day · Greenhouse

Job facts

FieldValue
CompanyScale AI
TitleInfrastructure Software Engineer, Enterprise GenAI
Normalized title-
Department / teamEnterprise Engineering
LocationSan Francisco, CA, United States
Work model-
Employment type-
Salary$216,000–$270,000 / day
Statusactive
ATS providerGreenhouse
Posted / first seen2026-02-24 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Scale AI.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Enterprise Engineering.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyScale AI
Source478b1bfa-4300-406a-af8f-46743fd1575c
ATS providerGreenhouse

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 Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision . PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

Full job record

Job IDc4ee8da13158a2f686a98ed2d8cde0b2a322b9e3
Org IDdb386fb1-bffb-4a23-880d-c7083d7a6694
Source ID478b1bfa-4300-406a-af8f-46743fd1575c
Board ID478b1bfa-4300-406a-af8f-46743fd1575c
Providergreenhouse
Provider Job Key4665557005
TitleInfrastructure Software Engineer, Enterprise GenAI
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco, CA; New York, NY
DepartmentEnterprise Engineering
Team
Employment Type
Workplace Type
Remote Policy
CountryUnited States
RegionCA
CitySan Francisco
Salary Rawsalary range for this full-time position in the locations of San Francisco, New York, Seattle is: $216,000 — $270,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period b
Salary Min216,000
Salary Max270,000
Salary CurrencyUSD
Salary Periodday
Source URLhttps://job-boards.greenhouse.io/scaleai/jobs/4665557005
Apply URLhttps://job-boards.greenhouse.io/scaleai/jobs/4665557005
First Seen At2026-05-29 22:40:44Z
Last Seen At2026-06-06 20:10:24Z
Last Checked At2026-06-06 20:10:24Z
Last Changed At2026-05-29 22:40:44Z
Inactive At
Source Posted At2026-02-24 00:15:38Z
Source Updated At2026-05-26 23:28:58Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=scaleai/date=2026-06-06/2026-06-06T20-10-23-787Z-6d82c7039f531644c5f888459c80edca53c38f0590093c71c74965c13481d850.json
Event Fields
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Parsed Structured
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  "salary_period": "day",
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  "salary_currency": "USD"
}
Extensions
{}
Native Structured
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  "company_name": "Scale AI",
  "requisition_id": 4345982005,
  "first_published": "2026-02-23T19:15:38-05:00",
  "application_deadline": null
}
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