Deployment Engineering Manager, Enterprise

At Scale AI, our mission is to accelerate the development of AI applications. For 10 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About our Enterprise Team: Our team owns the full deployment lifecycle of SGP in live customer environments — from initial rollout through long-term operational health. We work cross-functionally with customers, GTM, product, and infrastructure to ensure every deployment is production-ready, secure, and built to last. We’re looking for an Infrastructure Engineering Manager to help shape the future of AI-powered applications. In this role, you’ll bridge the gap between AI research and production, leading a team that is turning innovative prototypes into scalable, high-performance enterprise solutions. Your team will work on interactive AI applications, enterprise SaaS products, and platform capabilities that redefine how businesses leverage AI. We don't just ship and move on. We stay close to the customer experience, translating real-world deployment challenges into platform improvements, automation, and scalable playbooks that make every future rollout smoother than the last. If you're energized by solving complex technical problems at the intersection of customer impact and platform excellence, this is the team for you. Responsibilities: - Define and execute the infrastructure roadmap aligned with business and engineering priorities. - Lead the design and implementation of scalable, secure, and reliable infrastructure systems. - Set and maintain SLAs/SLOs for platform uptime, performance, and developer experience. - Manage the engineering team and drive technical delivery - Design, build, and optimize backend services for advanced AI-driven applications, focusing on AI agents, evaluation tooling, and automation - Influence the culture, values, and processes of a growing engineering team - Inspire and mentor engineers. - Work closely with product, security, and engineering leadership to align on goals and priorities. Requirements: - At least 5 years of relevant experience and at least 2+ years of experience managing infrastructure or platform teams. - Proven experience with cloud platforms such as AWS, GCP, or Azure. - Deep understanding of CI/CD pipelines, infrastructure-as-code (e.g., Terraform, Pulumi), and container orchestration (e.g., Kubernetes). - Experience managing production environments with high availability, reliability, and scalability requirements. - Familiarity with monitoring, alerting, and incident response best practices. - Experience working with modern developer platforms and internal tooling to improve engineering velocity. 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 and New York 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 & Youn

At least 5 years of relevant experience and at least 2+ years of experience managing infrastructure or platform teams. Proven experience with cloud platforms such as AWS, GCP, or Azure. Deep understanding of CI/CD pipelines, infrastructure-as-code (e.g., Terraform, Pulumi), and container orchestration (e.g., Kubernetes). Experience managing production environments with high availability, reliability, and scalability requirements. Familiarity with monitoring, alerting, and incident response best practices. Experience working with modern developer platforms and internal tooling to improve engineering velocity.

Define and execute the infrastructure roadmap aligned with business and engineering priorities. Lead the design and implementation of scalable, secure, and reliable infrastructure systems. Set and maintain SLAs/SLOs for platform uptime, performance, and developer experience. Manage the engineering team and drive technical delivery. Design, build, and optimize backend services for advanced AI-driven applications, focusing on AI agents, evaluation tooling, and automation. Influence the culture, values, and processes of a growing engineering team. Inspire and mentor engineers. Work closely with product, security, and engineering leadership to align on goals and priorities.