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Job Description & How to Apply Below
About the Role
As a Dev Ops 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.
Responsibilities- 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
, Cloud Formation
) 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.
- 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
, Java script
, 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.
- 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 No
SQL 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
.
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