Scale’s rapidly growing International 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
