Staff Infrastructure Software Engineer, Enterprise AI
Scale AI - New York, NY; San Francisco, CA
Posted Aug 20, 2025
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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Where they hire
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About this role
Staff Infrastructure Software Engineer, Enterprise AI New York, NY; San Francisco, CA Scale GP is building the infrastructure that makes enterprise AI seamless. We are looking for a Senior or Staff Infrastructure Engineer to act as a primary technical lead, engineering the 'paved road' for our knowledge retrieval and inference engines. You won't just be managing resources; you'll be defining the deployment standards for Agentic workflows at scale. Your mission is to bridge the gap between complex AI orchestration and world-class infrastructure, ensuring our platform remains the most reliable destination for enterprise agents The ideal candidate thrives in a fast-paced environment, has a passion for both deep technical work and mentoring, and is capable of setting a long-term technical strategy for a critical domain while maintaining a strong, hands-on delivery focus. You will architect and 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. - Use our own data and AI platform to analyze build and test logs and metrics to identify areas for improvement. - Define the architectural patterns for our multi-cloud infrastructure to support secure, reliable, and scalable Agentic workflows for enterprise customers. - Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection. - Collaborate with platform and product teams
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