DevOps Engineer, GPS

Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a DevOps Engineer, you will design and develop core platforms and software systems, while supporting orchestration, data abstraction, data pipelines, identity & access management, security tools, and underlying cloud infrastructure. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Backend Development and System Ownership: Design and implement secure, scalable backend systems for customers using modern, cloud-native AI infrastructure. Own services or systems, define long-term health goals, and improve the health of surrounding components. Collaboration and Standards: Collaborate with cross-functional teams to define and execute backend and infrastructure solutions tailored for secure environments. Enhance engineering standards, tooling, and processes to maintain high-quality outputs. Infrastructure Automation and Management: Write, maintain, and enhance Infrastructure as Code templates (e.g., Terraform, CloudFormation) for automated provisioning and management. Manage networking architecture, including secure VPCs, VPNs, load balancers, and firewalls, in cloud environments. Deployment and Scalability: Design and optimize CI/CD pipelines for efficient testing, building, and deployment processes. Scale and optimize containerized applications using orchestration platforms like Kubernetes to ensure high availability and reliability. Disaster Recovery and Hybrid Strategies: Develop and test disaster recovery plans with robust backups and failover mechanisms. Design and implement hybrid and multi-cloud strategies to support workloads across on-premises and multiple cloud providers. Ideally you’d have: A strong engineering background, with a Bachelor’s degree in Computer Science, Mathematics, or a related quantitative field (or equivalent practical experience) 5+ years of post-graduation engineering experience, with a focus on back-end systems and proficiency in at least one of Python, Typescript, Javascript, or C++ Extensive experience in software development and a deep understanding of distributed systems and public cloud platforms (AWS and Azure preferred) Track record of independent ownership of successful engineering projects Experience working fluently with standard containerization & deployment technologies like Kubernetes, Terraform, Docker, etc. Strong knowledge of software engineering best practices and CI/CD tooling (CircleCI, Github Actions) Solid foundation and real-world experience in network engineering Nice to haves: Experience working cross functionally with operations Experience building solutions with LLMs and a deep understanding of the overall Gen AI landscape Experience with data warehouses (Snowflake, Firebolt) and data pipeline/ETL tools (Dagster, dbt) Experience with authentication/authorization systems (Zanzibar, Authz, etc.) Experience with NoSQL document databases (MongoDB) and structured databases (Postgres) Experience with hybrid or on-prem systems Experience with orchestration platforms, such as Temporal and AWS Step Functions 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 t