Role Overview

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 Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

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:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.

Role Overview

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 Principal AI Ops Architect, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners.

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:

• Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies.
• Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment.
• Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability.
• Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks.
• Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again.
• Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials.
• Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases.

Ideally, you have:

• Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector.
• Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI.
• System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core.
• Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools.
• Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them.
• Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy.
• Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it.

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 custom LLMs
• Upskilling and advisory services to spread the impact of AI

As a Full Stack Software Engineer (Forward Deployed), you’ll collaborate directly with public sector counterparts to quickly build full-stack, AI applications, to solve their most pressing challenges and achieve meaningful impact for citizens.

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:

• Partner with public sector clients to scope, collect feedback and implement solutions for complex problems, including spending up to two weeks per month in client offices for feedback and delivery.
• Architect production-grade applications that integrate AI models with full-stack frameworks, managing everything from interactive UIs to backend APIs and systems. 
• Deploy and manage infrastructure within cloud environments, ensuring the highest levels of system integrity, security, scalability, and long-term reliability.
• Contribute to core platform features designed to be reused across diverse international client use cases.
• Partner with design, product, and data teams to build robust applications aligned with the broader technical architecture.

Ideally you’d have:

• Bachelor’s degree in Computer Science or a related quantitative field 
• 5+ years of post-graduation, full-stack engineering experience with demonstrated proficiency in React (required), TypeScript, Next.js, Python,  Node.js, PostgreSQL or MongoDB plus hands-on experience with Docker, Kubernetes, and Azure/AWS/GCP.
• Proven ability to architect scalable, production-grade applications with a strong handle on cloud environments and infrastructure health.
• Experience working directly within customer infrastructure to deploy, maintain, and troubleshoot complex, end-to-end solutions.
• A self-starting approach with the technical maturity to navigate ambiguous requirements and deliver reliable software.
• Driven async communication methodologies to reduce communication frictions

Nice to haves:

• Proficient in Arabic 
• Past experience working in a forward deployed engineer / dedicated customer engineer role
• Experience working cross functionally with operations
• Experience building solutions with LLMs and a deep understanding of the overall Gen AI landscape

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